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

No annotations provided, so the description carries full burden. It explains the autonomy levels (suggest, ask, auto) and what each does, and mentions the return includes command result, recovery attempts, and verification status. It does not disclose potential side effects beyond running the command, but given the nature of the tool, this is adequate.

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, well-structured paragraph. It leads with the core action, then provides usage guidance, then explains autonomy, then expected output, and ends with exclusions. Every sentence adds value without 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 no output schema, the description covers the return structure (result, recovery attempts, verification status). It also explains the three parameter options adequately. For a tool with three parameters and moderate complexity, this is nearly complete; a more detailed explanation of verification status could push it to 5.

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 100% with descriptions for all three parameters. The description adds value by explaining the autonomy levels in context ('suggest reports fixes only, ask requires confirmation, auto may apply safe fixes and retry') and the role of max_retries, though the schema already captures the basics. Scores above baseline 3 due to useful elaboration.

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 one local command with SAGE's failure-recovery loop. It specifies the verb 'run', the resource 'local command', and the unique feature 'failure-recovery loop', distinguishing it from siblings like sage_agentic_fix.

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?

Explicitly states when to use: 'development commands where automatic diagnosis and retry may help, such as tests or builds.' Also lists when not to use: 'Do not use for destructive commands, credential entry, production deploys, or external account changes.' This provides clear guidance for tool selection.

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 fully addresses behavioral aspects. It clearly states: 'Side effects are exactly the side effects of the command itself,' and lists the return fields (exit_code, compact output, run_id, purpose, agent metadata). This gives the agent a complete understanding of what to expect and the risks involved.

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 (about 60 words over three sentences) and front-loaded with the core action. Every sentence provides essential information: the main function, when to use it, what it returns, and safety warnings. There is no redundancy or extraneous content.

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 absence of annotations and output schema, the description is remarkably complete. It covers purpose, usage guidelines, behavioral traits (side effects), return values, and security warnings. This is sufficient for an agent to correctly invoke and understand the tool's behavior without needing additional 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?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds minimal additional meaning beyond the schema: it mentions the purpose label and lists categories (read, search, test, etc.), which are already enumerated in the schema. The only extra is noting that purpose 'improves ML failure prediction.' Thus, the description adds limited value over 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 the tool's primary function: 'Run one local shell command through SAGE with a purpose label.' This provides a specific verb (run) and resource (local shell command), and the mention of SAGE and purpose label distinguishes it from sibling tools like sage_explain_error or sage_suggest_fix, which handle error explanation and fix suggestions rather than direct command execution.

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 when to use the tool ('Use when you need command execution and want the result categorized') and when not to use it ('Do not use for secrets, credential prompts, or deployment unless explicitly requested'). This provides clear usage boundaries and alternative considerations, aiding the agent in correct selection.

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 fully carries the burden of behavioral disclosure. It explicitly states 'Read-only: does not run commands, edit files, or contact external services,' which is critical for an AI agent to understand safety. It also describes the return structure and behavior when the parameter is omitted. This is comprehensive and transparent.

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 with three sentences. The first sentence immediately states the purpose. Every sentence adds necessary information: purpose, usage, return structure, and behavioral constraints. 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 tool's simplicity (one optional parameter, no output schema, no nested objects), the description fully covers all needed aspects: purpose, when to use, behavior, parameter semantics, and return structure. The agent can reliably select and invoke this tool without ambiguity.

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 sole parameter 'command_id' is optional and has 100% schema description coverage. The description adds meaning beyond the schema: 'Omit to analyze the most recent failed command.' This clarifies the default behavior and the nature of the parameter, which is sufficient for correct invocation.

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: to explain why a previous SAGE command failed. It uses a specific verb 'explain' and resource 'why a previous SAGE command failed'. This distinguishes it from siblings like sage_suggest_fix (which suggests fixes) and sage_run_workflow (which runs workflows).

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 usage context: 'Use after a non-zero command exit before editing code or retrying.' It also clarifies when not to use by stating it is read-only. However, it does not explicitly mention alternative tools or provide exclusion criteria beyond the read-only nature, which would strengthen the 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?

Explicitly declares read-only behavior and that it reads a local database without executing commands, compensating for the absence of 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?

Three concise sentences front-load the core action, purpose, and key details 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 the simple schema and no output schema, the description fully covers the tool's purpose, return data fields, and safety profile.

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 already describes both parameters (limit, failed_only) with 100% coverage; description adds no additional semantic value for parameters beyond what schema provides.

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 lists recent SAGE command runs and explicitly connects to sibling tools (sage_show_raw, sage_explain_error, sage_suggest_fix), distinguishing its role as a lookup tool for run IDs.

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?

Directly advises to use this tool to find run_ids for specific sibling tools, but does not explicitly state when not to use it or what alternatives might exist.

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 covers key behaviors: ordering (newest first), ignoring junk directories, and capping output. It does not detail what junk directories are or confirm read-only nature, but the disclosed traits are valuable.

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 action, no fluff. Every word serves a 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?

Given no output schema, the description covers the tool's purpose and key traits. The lack of output format details is a minor gap, but the context is sufficient for an agent to use it 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 100%, so baseline 3. The description does not add new parameter semantics beyond what the schema already provides (e.g., pattern format, root default).

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 ('Find files by pattern'), includes specifics ('newest first, junk directories ignored, capped output'), and distinguishes it from sibling tools like sage_tree (recursive directory listings).

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 advises to 'Prefer over recursive directory listings,' providing a clear usage context. It could be improved by also mentioning when not to use (e.g., for content search, use sage_grep), but the guidance is sufficient.

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 carry the full burden. It discloses that results are compressed and grouped with exact paths and line numbers, but omits details like follow-symlinks, error handling, or performance limits.

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 brief sentences, front-loading the core purpose and a usage hint. No wasted words, earns its place.

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 exists, so the description should clarify return format. It states paths and line numbers are kept but not structure (e.g., text vs JSON) or behavior for no matches, leaving 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 75% (all parameters have descriptions), so the baseline is 3. The tool description adds no additional parameter-level information beyond what is already in 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 'Search files with compressed, grouped results' with specific output traits. Distinguishes from external tools rg/grep and implicitly from siblings by focusing on content search with grouping.

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?

Directly advises to prefer this tool over rg/grep when output may be large, providing a clear usage context. Lacks explicit when-not-to-use or alternatives for small outputs.

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?

Describes compression strategy but omits details like what 'outline + head with line references' means exactly. No annotation support, so description carries full burden; lacks clarity on return format and side-effect-free read 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 concise, front-loaded sentences with no redundancy. Every sentence adds value: first explains core function, second gives usage 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 no output schema and no annotations, description should explain return format and behavior more thoroughly. Mentions compression but lacks specifics on what 'exact' and 'outline + head' means for large files. Adequate but not comprehensive.

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 covers 100% of parameters with descriptions. Description adds context on overall behavior but does not enhance meaning of individual parameters beyond schema. Baseline 3 is appropriate.

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 reads files with SAGE compression, specifying behavior for small vs large files. Distinguishes from generic file readers like cat/type/Get-Content, implying it's the preferred tool for reading files in this 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?

Explicitly advises preferring this over cat/type/Get-Content to save context, giving a clear use case. Does not explicitly exclude alternatives like sage_show_raw, but context implies it's for compression benefits.

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 fully covers behavior: it returns success, per-step status, duration, compact output, and discloses side effects ('runs the workflow's local commands and may change files'). This adds significant transparency beyond what annotations would provide.

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 compact (5 sentences), front-loaded with the core purpose, and every sentence adds distinct value (use case, return, side effects, exclusion). No unnecessary 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?

Given no output schema, the description adequately explains return values and side effects. It covers the two parameters well. A slight gap: no mention of error handling if workflow doesn't exist, but overall sufficient for the tool's moderate 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 100%, and the description adds meaningful examples for workflow_name (test, lint, build, ci) and clarifies workflow_path usage ('Optional path... Omit to use the default'). This goes beyond the bare 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 tool runs a named local workflow through SAGE, listing concrete examples (test, lint, build, ci). It distinguishes this tool from siblings by focusing on structured workflow execution rather than individual shell calls.

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 gives clear when-to-use context ('when the project has a repeatable workflow and you want one structured result instead of several separate shell calls') and a specific exclusion ('Do not use for deployment unless the user explicitly requested deployment'). It does not explicitly name alternative sibling tools but provides strong 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?

Although no annotations are provided, the description includes a behavioral guarantee ('compression never destroys the original'), adding transparency. However, it omits details like read-only nature, required permissions, or error handling when run_id is invalid.

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 conveys the purpose and a key behavioral trait efficiently.

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 tool has one optional parameter and no output schema. The description explains the purpose and a guarantee, but does not describe what is returned (e.g., format, size). For a retrieval tool, this is 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?

With 100% schema description coverage, the parameter is already well-documented. The description adds minimal value by repeating 'by ID', but does not provide additional context 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 the tool recovers exact stored output of a previous run by ID, specifying the action and resource distinctly. It distinguishes from siblings like sage_get_history which likely show summaries rather than raw output.

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 implicitly indicates usage when you need raw output by run ID, but offers no explicit guidance on when to use this tool versus alternatives like sage_get_history or sage_explain_error. No exclusions or alternatives are mentioned.

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 burden. It clearly states the tool is read-only and never applies patches or runs commands, which covers key safety behavior. However, it doesn't mention error handling or response details.

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: three sentences front-loading purpose, usage, return value, and safety. Every sentence adds value with no redundancy or unnecessary 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?

Given the tool has one optional parameter, no output schema, and simple behavior, the description covers all essential aspects: purpose, usage context, return structure, and safety. It is complete for an AI agent to select and 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?

Schema coverage is 100%, with the schema already describing the optional command_id parameter and its default behavior. The description adds no additional parameter information, so baseline score of 3 is appropriate.

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 suggests safe next steps for a failed SAGE command, using a specific verb and resource. It distinguishes itself from siblings like sage_explain_error and sage_run_workflow by specifying when to use it and what it does.

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 advises to use after sage_explain_error when possible fixes are wanted without execution. It also clarifies that it is read-only and never applies patches, setting clear expectations and 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?

No annotations are provided, so the description bears full responsibility. It states 'compact depth-limited directory overview' implying read-only behavior and filtering, but lacks details on side effects, permissions, or rate limits. For a tool with no annotations, this is insufficient 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?

A single succinct sentence of 10 words communicates the core purpose without waste. Every word earns its place.

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, the description should hint at return values or format, but it does not. The tool has three optional parameters, yet the description gives no guidance on defaults or behavior. It is too minimal to fully inform an agent's decision.

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 low (33%, only root has a description). The tool description adds no parameter explanations beyond the schema, failing to compensate for the gap or clarify depth and limit 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 it provides a compact, depth-limited directory overview, contrasting with ls -R. However, it does not explicitly differentiate from sibling tools like sage_glob or sage_grep, missing a chance to clarify its unique role.

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 'instead of ls -R noise' gives clear context on when to use—when a less verbose view is needed. But it offers no when-not-to-use or alternative sibling tools, so it stops short of a 5.

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