Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It mentions creating a rollback checkpoint, indicating a safety feature, but fails to describe other side effects (e.g., state changes, permissions required, reversibility, error conditions). For a potentially destructive action, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence. However, it sacrifices important information for brevity. While no fluff, it does not earn its place fully because parameter details are missing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (mutation action), no output schema, no parameter descriptions, and no annotations, the description is insufficient for an AI agent to invoke the tool correctly and safely. Critical details about success/failure, idempotency, and prerequisites are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not explain the two UUID parameters 'proposalId' and 'approvalId'. Their difference and usage are unclear from the description alone, leaving the agent to guess their semantic roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the primary action ('apply') and the resource ('explicitly approved proposed patch'), with secondary action ('create a rollback checkpoint') that differentiates it from sibling tools like 'glm_5_approve_and_apply_changes' (which combines approval and apply) and 'glm_5_propose_patch' (only proposes). However, it could be more specific about what 'apply' entails.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. For example, 'glm_5_approve_and_apply_changes' might be a combined alternative, but no comparison or when-not usage is provided. Prerequisites (e.g., that approval must exist) are only implied by the parameter name 'approvalId'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses creation of rollback checkpoint and audit entry, plus that commands are not executed. However, no annotations exist, and it does not specify destructive potential, required permissions, or behavior on invalid proposals.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences covering the main action and key side effects. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and two simple UUID parameters, the description covers the primary behavior. However, lacks details on error handling, return values, or preconditions, making it moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage. Parameter names (proposalId, approvalId) are self-explanatory, but the description adds no additional context about expected formats, constraints, or relationships between them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool applies approved proposal changes, creates rollback checkpoint, and records audit. It distinguishes from siblings like apply_approved_patch by mentioning 'commands are not executed', but could be more specific about the difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like glm_5_apply_approved_patch. The description implies usage for applying approved changes but lacks when-not or alternative scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must fully disclose behavioral traits. It mentions preserving audit state but omits details on irreversibility, permission requirements, or what happens to already completed work. The single sentence is insufficient for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. However, it could benefit from slightly more structure (e.g., bullet points or separate sentences for key behaviors). It is concise but not a model of clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has three parameters, no output schema, and sibling lifecycle tools, the description is too sparse. It fails to specify return values, parameter details, or edge cases, making it inadequate for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not explain any of the three parameters (jobId, reason, rollbackIfPossible). Schema coverage is 0%, so it adds no meaning beyond the raw schema structure, leaving the agent uninformed about parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Cancel' and the resource 'future work in a persisted job', distinguishing it from siblings like 'resume_job' or 'rollback_changes'. It also adds the qualifier 'preserving audit state', which specifies a key behavioral aspect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as 'rollback_changes' or 'revoke_approval'. It does not mention prerequisites, exclusions, or preferred contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must fully convey behavioral traits. It only states 'compare' without explaining side effects, permissions, or output behavior, leaving significant ambiguity about what the tool actually does.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no unnecessary words. It is well-structured and easy to read.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and the minimal parameter information, the description is insufficient. It does not specify what the comparison produces or how the 'context' parameter is used, leaving the tool's overall functionality underdefined.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides no information about the parameters 'question' and 'context'. The schema coverage is 0%, and the description fails to explain how the parameters relate to the 'reasoning-oriented' and 'knowledge-oriented' answers mentioned, adding no value beyond the field names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'compare' and the resources 'reasoning-oriented GLM answer' and 'knowledge-oriented answer', making the purpose specific and distinguishable from sibling tools that focus on consultation or routing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as glm_5_consult_knowledge or glm_5_query_reasoning. There is no mention of prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It only states that this tool is for consultation and not task execution, but does not mention side effects, permissions, rate limits, or output behavior. Important traits like whether the call is read-only or has any safety implications are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the core purpose. It avoids unnecessary words but could benefit from a brief list of key parameters or usage hints without adding much length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 8 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on parameter usage, return values, and behavioral constraints, making it incomplete for an agent to use effectively without prior knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 8 parameters with 0% description coverage, and the tool description provides no additional explanation for any parameter. For instance, 'domain', 'context', 'outputFormat', 'responseMode', and others are not explained, leaving the agent to infer their meaning from names alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'consult' and the resource 'GLM' for knowledge purposes. It explicitly lists use cases (expert explanation, second opinion, architecture advice, unfamiliar concept) and distinguishes this tool from task execution, making it easy for the agent to understand its primary function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit negative guidance ('not task execution'), which helps differentiate from many sibling tools like glm_5_execute_development_task. However, it does not name specific alternative tools for related use cases, missing a direct comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must carry full burden. It notes that 'Contexts never include API keys', which is a useful safety guarantee. However, it does not disclose other behavioral aspects such as persistence scope, concurrency effects, or required permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is front-loaded with the core purpose. Every word adds value, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, no output schema, and no annotations, the description is too sparse. It omits essential details like what a context contains, how it interacts with project paths, and how tags are used. The tool's role in workflow or project management is unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description should compensate by explaining parameter roles. It only mentions the tool's overall actions and fails to describe how parameters like name, content, contextId, or tags relate to specific actions. The action enum is self-explanatory, but other parameters remain undefined.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool performs CRUD operations on 'reusable local project contexts', with a specific verb list. However, it does not differentiate from sibling tool 'inspect_project_context' which may overlap for read operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'inspect_project_context' for read-only access. The description only states what it does, not when to prefer it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description adds value by stating the tool only proposes and does not execute host tools. However, it omits other behavioral traits such as side effects, idempotency, or required permissions, leaving gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (two sentences) and front-loaded with the core action. It avoids fluff but could include more informative details without sacrificing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 4 parameters, no annotations, and no output schema, the description is too brief. It does not explain return values, error conditions, or the format of proposals, leaving the tool underspecified for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description fails to map its concepts ('objective', 'compact prior summary') to specific parameters like sessionId or instruction. It provides no parameter-level details, leaving the agent to infer meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it continues a 'persisted agentic task' using its objective and summary, which is specific. It distinguishes from siblings like 'resume_job' by noting it proposes and does not execute host tools, though sibling differentiation is not explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a persisted task exists and needs continuation, but lacks explicit guidance on when not to use or comparison with alternatives like 'resume_job' or 'route_agentic_task'. The 'proposes only' hint is useful but not comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Mentions validation and bounded types, but lacks details on side effects, permissions, or state changes. No annotations to rely on.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, immediate verb, no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No mention of return value, idempotency, or what 'local' means; insufficient for a complex tool with 4 required parameters including nested objects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds meaning by referencing validated step dependencies and bounded step types, which maps to 'dependsOn' and 'type' enum, compensating for 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action ('Create') and the resource ('reusable local workflow definition'), and distinguishes from siblings like 'run_workflow'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use vs alternatives; context likely inferred from sibling tools but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the core action without detailing side effects, return values, rate limits, or any constraints beyond 'without executing.' This leaves significant uncertainty.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise, but it sacrifices necessary detail. While front-loaded with purpose, it is under-specified given the tool's complexity (2 params, no output schema). It could be longer to include key guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema, zero parameter descriptions, and no annotations, the description is severely incomplete. It does not explain the return format, behavior with invalid input, or provide any usage context beyond the bare action.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% – the schema provides no parameter descriptions. The description adds no information about what 'request' or 'imagePath' represent, their formats, or how they affect the output. This is a critical gap for a tool with two parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Score likely routing modes') and distinguishes it from executing the routed tool. It is specific and differentiates from sibling tools like smart_route and route_agentic_task, which actually perform routing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lacks explicit guidance on when to use this tool versus alternatives. It only mentions 'without executing,' implying evaluation before routing, but does not state prerequisites, when not to use it, or name alternative tools for different scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explicitly states 'No mutation occurs automatically', which is a critical behavioral trait not covered by annotations (none provided). However, it omits many other important behaviors like approval flows, side effects of creating a job, and how different modes affect execution.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two sentences, making it concise and front-loaded with the core purpose. However, given the tool's complexity (9 params, many siblings), it is too brief and sacrifices necessary detail for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is incomplete given the tool's complexity, lack of output schema, and no annotations. It fails to explain the orchestration workflow, parameter relationships, or expected outcomes. The sibling list is long but the description itself provides insufficient context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds no information about any of the 9 parameters. It doesn't explain 'mode', 'roles', 'maxAgentRuns', or other fields. The agent is left to infer parameter meanings from names alone, which is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool creates an 'auditable development orchestration plan' using a 'safe development workflow surface', which clearly indicates its purpose. However, it does not explicitly differentiate from siblings like 'glm_5_plan_code_change' or 'glm_5_orchestrate_project_task', so it's not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus the many siblings. The only hint is 'No mutation occurs automatically', which implies safety but doesn't specify alternatives or prerequisites. The agent lacks context for correct invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It adds useful context: exports are safe, exclude secrets and raw source files. However, it doesn't mention auth requirements, rate limits, or other behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, lists content efficiently. No fluff, but could benefit from a bullet list or a note about parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 undocumented parameters and no output schema, the description is insufficient. It omits what each include flag does and the output format, making it hard for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All six boolean parameters are optional with no schema descriptions (0% coverage). The description does not mention any parameter, leaving the agent to guess what each include flag controls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'export' and the resource 'safe persisted bridge state', listing examples of content. However, it does not explicitly differentiate from sibling tools like glm_5_import_project_state or inspect tools, relying on the verb difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, e.g., when to export vs inspect or import. No prerequisites or context provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, and the description only hints at constraints (network enablement, domain allowlist) but does not disclose error behavior, return format, rate limits, or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with the core action, but very minimal; could add more detail without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter tool with no output schema, the description lacks details on return values, error states, and behavior when conditions are not met, making it barely adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the 'url' or 'allowRedirects' parameters beyond the schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the action ('Fetch an external HTTPS reference') and adds contextual constraints (network enabled and allowlisted domain), making the purpose distinct from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives; no exclusions or when-not-to-use advice provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavior. It notes 'safe' and 'dry-run enabled by default,' implying safety. However, it does not explain consequences of actual import (e.g., overwrite behavior) or any destructive potential.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise: single sentence. While efficient, it could be slightly more structured to improve readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, 3 params with nested objects, the description is insufficient. It lacks details on payload requirements, overwrite effects, and return behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% (no descriptions in schema). Description adds minimal meaning: mentions 'validated payload' and dry-run default, but does not explain the payload structure or overwrite parameter beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it imports safe persisted bridge state from a validated payload and mentions dry-run default. This distinguishes it from related tools like export_project_state, though 'bridge state' could be clarified.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives like export or apply. The description only states the action and default dry-run, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. 'Inspect' implies read-only, but no explicit confirmation of safety or side effects. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence is concise, but lacks structure. It could include parameter details without excessive length. Balanced between brevity and completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, no parameter descriptions, and no behavioral details. The description is insufficient for a tool with 3 parameters and no annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description adds no information about parameters (jobId, includeTaskGraph, includeAuditSummary). With 0% schema coverage, this is a critical gap, leaving agent to guess semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it inspects a persisted orchestration job and its safe task graph status, using specific verb and resource. It distinguishes from siblings like inspect_workspace or inspect_project_context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives, no mention of prerequisites or exclusion criteria. The description gives no context for use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It conveys 'read-only' and 'bounded' behavior, but does not explain permissions required, error handling for unapproved directories, or what 'bounded' entails beyond maxDepth parameter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence efficiently conveys core purpose and scope. No redundant words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, no output schema, and no annotations, the description provides only a high-level overview. Missing details on parameter behavior, return format, and failure modes, making it insufficient for complete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. Description does not explain individual parameters (e.g., maxDepth, includeFileTree) beyond their names. No details on how projectPath validation works or effects of boolean flags.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool's function: 'safely inspect an approved local project directory' and lists the types of information retrieved (file metadata, tree, package, Git-summary). It distinguishes from sibling tools like inspect_job and inspect_workspace by specifying 'project directory' and 'read-only bounded'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies usage for inspection but lacks explicit guidance on when to use this tool vs alternatives. Does not mention prerequisites like 'approved' status or context for selecting this tool over similar inspect tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavioral traits. It does not disclose that the 'upsert' action modifies data, nor any permissions, rate limits, or side effects. The description only highlights metadata presence.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no unnecessary words. Efficiently conveys the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 9 parameters and no output schema, the description is too brief. It omits explanation of the 'action' parameter (especially the 'upsert' capability) and return value structure, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description needs to compensate. It adds context about 'provenance, confidence, and status metadata', which hints at parameter usage but does not explain individual parameters or their roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb (list/inspect) and resource (repository memory entries). It distinguishes from sibling update_repository_memory by focusing on inspection rather than modification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs. alternatives. The description mentions only 'list or inspect' but the schema includes an 'upsert' action, creating confusion about the tool's full usage scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description bears full burden. It implies a read-only operation (inspect), but does not explicitly state it is non-destructive or disclose any side effects, requirements, or limitations. Adequate but not explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence that is clear and direct. No unnecessary words, front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description lacks details about return values, error conditions, or success/failure indicators. It mentions what the tool inspects for but not what is returned, making it only partially complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must compensate. It indicates workingDirectory refers to the repository root path, adding value beyond the parameter name. However, it does not specify path format, validation, or expected contents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool inspects a repository or monorepo root for workspace signals, package manifests, and layout metadata. This specific verb+resource combination distinguishes it from sibling inspection tools like inspect_job or inspect_project_context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as glm_5_inspect_job or glm_5_inspect_project_context. The description implies a context (repository inspection) but lacks exclusions or comparative context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description bears full responsibility for behavioral disclosure. It specifies that it lists proposals requiring 'exact matching approval,' indicating a read operation and a specific condition. It does not mention non-destructive nature, but 'list' implies safety. A score of 4 reflects good transparency given no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that front-loads the purpose and includes the essential condition. Every word earns its place with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, no output schema, and a simple list operation, the description sufficiently covers what the tool does and the condition for the listed items. No additional context is necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no parameters (schema coverage 100%), so the description does not need to add parameter meaning. Baseline is 4, and the description correctly provides no extraneous parameter info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's function: list pending change proposals that require exact matching approval. It distinguishes this from sibling tools like 'glm_5_propose_changes' (proposing) and 'glm_5_apply_approved_patch' (applying), establishing a unique resource and condition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used when checking for pending approvals needing exact matching, but it does not explicitly state when not to use it or list alternative tools for different scenarios. It provides adequate context without exclusions or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It labels profiles as 'auditable' but does not mention permission requirements, idempotency of upsert, potential destructive behavior (e.g., deleting policies), side effects, or error conditions. The single sentence is insufficient for a tool controlling critical security settings.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise and front-loads the action and resource. However, for a tool with 16 parameters and 3 actions, the brevity comes at the cost of completeness. It could be restructured with bullet points or expanded slightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high complexity (16 parameters, no schema descriptions, no output schema, no annotations), the description is severely underdeveloped. It provides only a high-level purpose and fails to explain parameter usage, action semantics, defaults, or response behavior. The tool is not usable without additional documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It groups parameters into control areas (writes, commands, network, privacy), which loosely maps to some parameters (e.g., allowWrites, allowCommands), but many parameters (allowFileDeletion, maximumAgentRuns, requireApprovalForWrites, etc.) are not mentioned. No parameter-level details are provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the resource (auditable policy profiles) and actions (inspect/upsert), and outlines the controlled areas (writes, commands, network access, privacy). It distinguishes from sibling tools which focus on other aspects like patches or approvals, though it could more precisely align 'inspect' with the schema actions 'get' and 'list'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, nor any exclusions. The description does not explain when to choose 'get', 'list', or 'upsert', nor does it mention prerequisites or ideal scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears full weight. It discloses key behaviors: it creates plans, is role-specific, dependency-aware, and requires approval for file mutations. However, it omits details on authentication, rate limits, output format, or what happens to existing plans.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose. No fluff. Could expand without harming conciseness, but it is efficient for the given information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 parameters, no output schema), the description is inadequate. It does not cover return values, lifecycle, role interactions, or any behavioral expectations beyond the non-mutation note. Significant gaps remain for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description adds no meaning to any of the 9 parameters. It does not explain 'mode', 'roles', 'objective', etc., leaving the agent to rely solely on the schema, which lacks descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates an auditable, role-specific, dependency-aware development plan/job. It uses a specific verb ('create') and identifies the resource. However, it does not explicitly differentiate from similar sibling tools like 'plan_code_change' or 'create_workflow', leaving some ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description only notes it never mutates files without approval, which hints at a safety condition but does not provide context for selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses non-mutating behavior and approval gate, but no details on what 'persist' means, side effects, or error conditions. Without annotations, more behavioral context would be helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence efficiently conveys purpose, but is not structured for easy scanning. Appropriate length given complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Incomplete for a planning tool in a workflow. No output schema, no description of return values or how to use the persisted plan. Lacks details to differentiate from siblings like propose_patch.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description adds no parameter explanations. Parameter names are somewhat self-explanatory, but the description should clarify constraints, especially for operations and commands.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'plan's an approval-gated code change' and specifies it persists operations without mutating the repository, distinguishing it from mutation tools like apply_approved_patch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by contrasting with application tools, but no explicit when-to-use or when-not-to-use guidance is given beyond the name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It correctly states it never mutates files or executes commands, but does not disclose other behaviors like persistence duration, approval flow details, or error handling. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. The first sentence defines the purpose, the second adds critical constraints. Well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain how to structure operations, the meaning of summary, or what happens after proposal creation. The agent lacks sufficient contextual detail to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no information about parameters such as 'summary', 'operations', 'commands', or 'workingDirectory'. The agent must rely solely on the schema, which lacks descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it creates a persistent, reviewable file-change proposal, and explicitly distinguishes from siblings by noting it never mutates files or executes commands. This is a specific verb+resource with clear differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states that the tool does not mutate files and requires approval, guiding the agent to use it for proposals only and not for direct changes. It could be more explicit about alternatives like 'apply_approved_patch' but is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses that files are not changed until approval, which is key behavioral info. However, it omits details on authorization needs, rate limits, or how the proposal is stored/retrieved.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at two sentences, with no wasted words. It front-loads the core action and immediately addresses the key constraint (no file changes until approval).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain what the tool returns or how to track the proposal. It lacks info on constraints like maximum items for operations/commands and does not mention expected output or follow-up steps, making it incomplete for complex usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not explain any parameters. While parameter names are somewhat self-explanatory, the description fails to clarify the structure of 'operations' or the role of 'commands', leaving the agent to rely solely on schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Propose' and the resource 'scoped patch', distinguishing it from sibling tools like apply or approve. It explicitly notes that no files are changed until later approval, which differentiates it from direct modification tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates when to use this tool (proposing a reviewable patch) and clarifies the non-destructive nature. It implies a two-step process (propose then approve), but does not explicitly mention alternatives or conditions when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description is the sole source. It mentions 'provider-supported reasoning' but fails to disclose cost, latency, rate limits, or failure behavior. Minimal transparency for a tool that likely involves significant processing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single, clear sentence with no extraneous words. However, it could be more structured by front-loading the most critical information (e.g., that this is for deep reasoning, not simple queries).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, no output schema, and no annotations, the description is too sparse. It does not cover return values, error handling, or typical use scenarios, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain any parameter. Parameter names like 'reasoningBudget' and 'comparePerspectives' hint at purpose, but the description adds no value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'resolve' and specifies types of bottlenecks (technical, systems, debugging, etc.). However, it does not differentiate from siblings like glm_5_execute_development_task or glm_5_smart_route, which could also handle similar reasoning tasks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage for difficult reasoning problems, but no explicit when-to-use or when-not-to-use. No alternatives mentioned despite many sibling tools with overlapping capabilities.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses that the tool revokes the previous token (destructive), but does not mention permissions, reversibility, or side effects. Minimal behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single concise sentence front-loading the purpose. While brief, it contains no filler and earns its place. Could benefit from additional context without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 0% schema coverage, no output schema, and no annotations, the description is incomplete. It does not explain prerequisites, order of operations, return value, or the relationship between parameters. Leaves significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and description adds no parameter-level details. Parameters 'proposalId', 'approvalId', and 'reason' are unexplained in both schema and description. 'reason' has constraints (min/max length) but not described.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'reissue' with 'approval ID' and 'current proposal revision', clearly distinguishing from sibling tools like 'revoke_approval' or 'list_pending_approvals'. It states the action and its effect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage when a fresh approval ID is needed while revoking the previous one, but no explicit when-to-use or when-not-to-use guidance is given. Siblings like 'revoke_approval' are not mentioned as alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden; it discloses non-mutating and approval-gating but lacks details on side effects, return values, or state transitions after resuming.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one concise sentence that front-loads the core action and constraints, but it could be restructured to include parameter hints without losing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 0% schema coverage, no output schema, and no annotations, the description is insufficient for an agent to use the tool correctly; missing parameter details and return behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not mention any parameter, leaving jobId, approvalId, and additionalInstruction unexplained; agents must guess their purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool resumes a job in a planning state, specifying it's non-mutating and approval-gated, which distinguishes it from mutation-focused siblings like apply_approved_patch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives like continue_task or cancel_job, nor does it provide prerequisites or exclusions; usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. The description implies a read-only inspection ('inspect') without side effects, but does not explicitly confirm non-destructive behavior or mention permissions/rate limits. Adequate but could be more explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no unnecessary words. It efficiently conveys the tool's purpose and usage context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple inspection tool with one parameter and no output schema, the description covers the what and when. It hints at the output ('audit trail') but does not detail return structure, which is acceptable given the low complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description adds no details about the 'proposalId' parameter beyond its type (UUID). It does not explain its role or format, so the agent lacks guidance despite a single parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'inspect' and the resource 'proposed change set' with 'audit trail', distinguishing it from siblings like 'propose_changes' and 'approve_and_apply_changes'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'before approval or rollback' explicitly indicates when to use this tool. While no direct exclusion or alternative naming, the context is clear given sibling tools for approval and rollback.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It only states 'without applying mutation' but lacks details on side effects, permissions, or state changes. Minimal behavioral disclosure for a mutation-adjacent tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no fluff. Efficient but borderline too concise given missing information. Slightly penalized for completeness trade-off.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, no annotations, and 3 parameters, description is inadequate. Does not explain approval workflow, how to obtain approvalId, or consequences of revocation. Lacks sufficient context for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage 0% and description adds no meaning to parameters. Does not explain proposalId, approvalId, or reason. Agent gets no help understanding what values to provide or their roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states specific verb 'revoke' and resource 'current approval token', and adds 'without applying mutation' which distinguishes it from sibling tools like approve_and_apply or propose_changes. Very clear purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage context (revoke token without mutation) but no explicit guidance on when to use this vs alternatives like reissue_approval or apply_approved_patch. Missing when-not scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description provides some behavioral information: it requires an explicit matching approval token and only restores files in the working directory. But it omits details on side effects (e.g., whether the checkpoint is consumed), idempotency, or authorization requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is just two sentences, tightly scoped. The first sentence states the main purpose, and the second adds a crucial constraint. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (3 required UUID parameters, no output schema, no annotations) and the existence of similar siblings, the description is too brief. It does not explain what a proposal checkpoint is, what constitutes a matching approval token, or the post-restoration state, leaving gaps for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has three parameters with 0% description coverage. The description indirectly implies the need for proposalId, checkpointId, and approvalId but does not explain their individual roles or formats beyond the schema. The agent may infer, but the description adds minimal semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Restore' and the resource 'proposal checkpoint', and specifies the scope 'only restores files in the proposal's working directory'. It distinguishes from the sibling 'glm_5_rollback_change_set' by emphasizing the need for an explicit matching approval token.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used after obtaining an explicit matching approval token, offering some context. However, it does not explicitly state when not to use it or name alternatives like 'glm_5_rollback_change_set' or 'glm_5_revoke_approval'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must carry the burden. It mentions restoring a checkpoint in the working directory but does not disclose whether it is destructive, reversible, or what permissions are needed. The behavioral impact is under-explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single 14-word sentence that immediately states the action and mechanism. It is concise and front-loaded, though it sacrifices completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given three required parameters, no output schema, no annotations, and a sibling tool with similar name, the description is incomplete. It does not provide enough context for an agent to reliably select and invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the meaning of the three parameters (proposalId, checkpointId, approvalId). It lacks any semantic guidance on how they relate to the change set or checkpoint restoration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the action (roll back), the resource (applied change set), and the mechanism (restoring its checkpoint inside the approved working directory). It distinguishes from the sibling 'glm_5_rollback_changes' by focusing on change sets and checkpoints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like glm_5_rollback_changes or glm_5_review_change_set. The description does not mention contexts, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It clearly states that the tool proposes but never executes host tools, which is critical behavioral info. However, it omits other traits like whether it modifies state, requires approvals, or returns intermediate results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (one sentence) and front-loaded with the action verb 'Delegate'. However, it is too brief for a tool with 7 parameters and many siblings, sacrificing necessary detail for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 params, many siblings, no output schema), the description is severely incomplete. It does not explain return values, session management, relationship to other tools, or preconditions. The agent would lack needed context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 7 parameters (e.g., maxSteps, contextCode, sessionName) with 0% schema description coverage. The tool description provides no explanations for any parameter, leaving the agent without crucial guidance on how to populate them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: delegate multi-step planning, implementation proposals, debugging, migrations, or refactors to GLM. It explicitly distinguishes itself by noting that GLM proposes but never executes host tools, differentiating it from siblings that likely involve execution or approval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for complex multi-step tasks, but provides no explicit guidance on when to use this tool versus the many siblings (e.g., glm_5_plan_code_change, glm_5_propose_changes). No when-not-to-use or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions the command must be allowlisted and approved, but lacks details on side effects, failure modes, authentication requirements, or return behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with front-loaded purpose and a key constraint. No unnecessary words; every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 required parameters, no output schema, and no annotations, the description is too brief. It omits important context about what the command returns, what constitutes approval, and behavior on failure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage. The description adds context that the command enum values are 'allowlisted project validation commands', but does not explain workingDirectory, approvalId, or proposalId, leaving their semantics unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it runs an allowlisted project validation command after approval, distinguishing it from arbitrary execution. However, it does not explicitly differentiate from sibling tools like glm_5_execute_development_task or glm_5_run_controlled_agent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage requires prior approval ('after explicit matching approval') and prohibits arbitrary commands. It does not mention when to use alternatives or provide explicit when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behavioral traits: read-only, bounded, no file writes or arbitrary commands. However, without annotations, more details (e.g., error handling, return behavior) would be needed for full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, very concise and front-loaded. However, given the tool's complexity (7 parameters, no annotations), additional detail would be warranted; this borders on under-specification.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Considering the parameter count (7), lack of annotations, missing output schema, and 0% schema coverage, the description is insufficiently complete. It does not explain how to configure the tool or interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description provides no information about parameters like task, dryRun, context, allowedTools, etc. The description fails to add meaning beyond the schema's bare structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs a bounded, read-only GLM tool-use loop within an approved directory, and explicitly notes it cannot write files or run arbitrary commands. This differentiates it from siblings like glm_5_run_approved_command and glm_5_apply_approved_patch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided on when to use this tool versus alternatives. The description does not mention when-not to use or which sibling to choose instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It mentions 'auditable planning job' and optional quality gates, but omits whether the operation is read-only or destructive, what side effects occur, required permissions, or error conditions. The description adds minimal transparency beyond the bare action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences – very concise and front-loaded with the primary action. The second sentence adds an optional capability. However, the brevity sacrifices clarity on required parameters and usage context, making it less helpful despite being short.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters (3 required), no annotations, and no output schema, the description is severely incomplete. It fails to explain how to specify the workflow, what 'creates a job' entails, how approval/proposal IDs relate, or what the return format is. The tool is complex enough to demand a richer description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning parameters lack descriptions. The description adds value only for workflowId (implied) and quality gates (explicitly named). Parameters like objective, workingDirectory, approvalId, proposalId, and createJob are not explained. The agent must guess their roles from schema names and types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the main action and resource: 'Instantiate a reusable workflow as an auditable planning job.' It distinguishes from siblings like glm_5_create_workflow by focusing on instantiation rather than creation. The mention of optional quality gates adds behavioral nuance, but lacks explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. For example, sibling tools like glm_5_execute_development_task or glm_5_plan_code_change may overlap in purpose. The description does not specify prerequisites (e.g., workflow must exist) or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavior. It mentions determinism and no recursion but omits failure handling, output format, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence is concise but lacks structure. It is front-loaded with the core purpose, but important details are missing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, no output schema, and no annotations, the description is severely incomplete. An agent would lack critical usage details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description adds no meaning to any of the 5 parameters. Parameters like context, imagePath, and preferredMode are completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it routes requests to specific modes (vision, agentic planning, reasoning, knowledge), with a deterministic approach and no recursion, distinguishing it from direct sibling tools like consult_knowledge or query_reasoning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus calling the individual mode tools directly. The benefit of deterministic routing is implied but not explained.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds a behavioral constraint: 'Confirmed facts require explicit provenance; inference must remain marked accordingly.' This provides useful context about data integrity, but lacks details on mutations, idempotency, or authentication needs. With no annotations, the description carries the full burden and only partially meets it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no redundant words. It conveys essential behavioral nuance without waste, earning maximum conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, multiple enums, no output schema), the description is too brief. It omits crucial details like the supported actions, status semantics, category purposes, and return behavior, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 9 parameters, the description must compensate but does not. It mentions provenance and inference marking, which loosely relate to the 'provenance' and 'status' parameters, but fails to explain the 'action', 'title', 'content', 'category', 'memoryId', 'confidence', and 'evidenceIds' meanings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Create or update repository memory entries', which clearly identifies the verb and resource. It distinguishes from the sibling 'glm_5_inspect_repository_memory' (read-only), but does not mention the 'get' and 'list' actions also available in the input schema, slightly reducing clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives like 'inspect_repository_memory', nor does it mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full responsibility. It indicates the tool uses a vision model to audit an image, suggesting a read-only analysis. However, it does not disclose potential side effects, authorization needs, or rate limits, leaving gaps in behavioral understanding.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks structural elements like bullet points for parameters. It could be more informative without adding length, given the tool has five parameters and no annotations or output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With five parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain return values, the meaning of 'audit', or how the vision model processes the image, leaving significant gaps for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not mention any of the five parameters. With 0% schema description coverage, the description fails to add meaning beyond the schema, such as explaining 'severityThreshold' or 'outputFormat'. This makes it hard for an agent to invoke the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'audit' and the resource types (local PNG, JPEG, etc.) against an objective using a vision model. It is specific and distinguishes this tool from siblings, which are not about image auditing. However, it does not clarify what 'audit' entails (e.g., generating a report).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description implies it is for auditing visual designs, but it does not mention when not to use it or compare with sibling tools like query_reasoning or consult_knowledge.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.