memcp

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

No annotations present, so the description carries the burden. It discloses the prerequisite (name must be loaded) and strategy options, but does not mention side effects, error behavior, or whether the operation is read-only.

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 short, front-loaded with the purpose, and efficiently uses bullet-style parameter definitions. Every sentence provides necessary 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 tool has 4 parameters (1 required) and an output schema, the description covers parameter semantics and prerequisites. It could mention that output provides chunk indices, but likely the output schema handles that.

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 value by explaining each parameter's meaning (e.g., size units per strategy). Some details like default behavior for chunk_size=0 could be clearer.

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 'split' and resource 'stored context into navigable numbered chunks'. It is specific and distinguishes from siblings like memcp_peek_chunk which likely views chunks.

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 context (splitting a loaded context) and explains parameters, but does not explicitly state when to use this over alternatives or provide 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?

The description discloses the destructive nature (deletion) and that associated chunks are removed, but with no annotations, it lacks details on side effects, reversibility, or permissions. This is adequate but not comprehensive.

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, using only two sentences to convey the tool's purpose and parameter, with no redundant or irrelevant 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?

While the description covers the basic action and parameter, it does not address return values, error conditions, or the state after deletion, leaving some gaps given the lack of 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?

With 0% schema description coverage, the description adds value by explaining the single parameter 'name' as 'Context name to delete', clarifying its role beyond the bare schema definition.

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 function with a specific verb ('Delete') and resource ('stored context and its chunks'), making its purpose unambiguous and differentiating it from sibling tools like memcp_forget.

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 (e.g., memcp_forget), nor are there any usage conditions or exclusions 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?

In the absence of annotations, the description effectively discloses key behavioral traits: it merges, keeps the best insight, merges tags/entities, redirects edges, and deletes duplicates. It lacks explicit mention of whether the operation is destructive or reversible, but the core behaviors are clear.

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, with a clear front-loaded summary followed by a parameter list. Every sentence earns its place; there is no redundancy or unnecessary 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 of a consolidation tool, the description provides a solid overview. It covers the main actions and parameters. Minor gaps include how the 'most accessed' default is determined, but overall it is sufficiently complete for typical 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?

With 0% schema description coverage, the description compensates well by explaining the role of each parameter (group_ids, keep_id, merged_content) in the docstring. This adds significant meaning 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's purpose: merging similar insights into one. It specifies the actions (keeping best insight, merging tags/entities, redirecting edges, deleting duplicates), making it distinct from sibling tools like memcp_remember or memcp_forget.

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 merging multiple similar insights but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. There is no guidance on prerequisites or when consolidation is inappropriate.

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 convey all behavioral traits. It states 'Dry-run — no changes made,' which successfully indicates safety. However, it lacks details on behavior under extreme inputs, error conditions, or performance characteristics. The description is 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?

The description is concise and well-structured: a brief purpose statement, a dry-run note, a clear sibling reference, and a cleanly formatted parameter list. Every sentence adds value, and the structure facilitates quick comprehension.

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 is a preview with an output schema (assumed to describe return values), the description covers the essential: purpose, dry-run nature, sibling relationship, and parameter explanations. It is complete enough for an agent to use correctly, though additional notes on group formation criteria could help.

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 description coverage is 0%, so the description compensates by explaining parameters in an 'Args' section. It clarifies that threshold=0 uses default 0.85, limit is max groups, and project filters by project. These explanations add meaning beyond the schema, though they could be more detailed (e.g., valid ranges).

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: 'Preview groups of similar insights that could be merged.' It specifies the action (preview), resource (groups of similar insights), and distinguishes from the sibling tool 'memcp_consolidate' by noting it's a dry-run and directing users to use the sibling for merging.

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 the tool is a dry-run and advises 'Use memcp_consolidate to merge.' This provides clear context for when to use this tool versus the alternative. However, it doesn't elaborate on scenarios where this tool should be preferred or prerequisites.

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 discloses the filtering behavior and the invert option, but does not mention side effects (none apparent), authorization needs, or error conditions. It is 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?

The description is front-loaded with the core purpose in one sentence, followed by a clear statement of behavior, then a terse docstring-style parameter list. No fluff; every sentence 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?

Given the existence of an output schema (not shown), the description need not detail return values. It covers the main functionality adequately. Minor gaps: no mention of required parameter validity or error handling, but acceptable for a simple filter 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%, so the description must compensate. It explains all three parameters: name ('Context name'), pattern ('Regex pattern to match lines'), and invert ('If True, return lines that DON'T match the pattern'). This adds meaning beyond the schema's bare titles.

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 'Filter', the resource 'context content', and the mechanism 'by regex pattern'. It distinguishes from siblings like memcp_get_context (which returns entire context) and memcp_search (which likely searches across contexts).

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 explains what the tool does (filters lines by regex) but does not explicitly state when to use it versus alternatives like memcp_get_context or memcp_inspect_context. It lacks usage context 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 exist, so the description must convey behavioral traits. It only says 'Remove an insight' without disclosing side effects (e.g., permanence, cascading effects, or error cases). This is insufficient for a deletion 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?

The description is extremely concise: two sentences plus parameter list, with the key action front-loaded. No extraneous 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 single parameter and output schema, the description covers basic functionality but lacks details on idempotency, error handling, or confirmation steps. Adequate for a simple deletion but not fully 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 the description adds value by explaining 'insight_id: The ID of the insight to remove'. While minimal, it clarifies the parameter's role beyond the schema's type and title.

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 ('Remove') and resource ('insight from memory'), and the tool name 'forget' complements this. It distinguishes from siblings like 'memcp_remember' (add) and 'memcp_recall' (retrieve).

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 vs alternatives, when not to use it, or any prerequisites. The agent gets no context about appropriate usage.

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, and the description does not disclose any behavioral traits such as side effects, error handling, or permissions. The word 'Read' implies idempotency, but no further detail is given about behavior when the context does not exist or when line ranges are 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 brief and to the point, with a clear purpose statement followed by parameter descriptions. However, it could be slightly more concise by integrating the parameter explanations into the main sentence, and it does not use formatting to highlight key constraints.

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 3 parameters (1 required) and an output schema, the description covers the input semantics well but omits return value explanation and error scenarios. The presence of an output schema reduces the need to describe return details, but overall completeness is moderate.

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 explains all three parameters (name, start, end) with semantic details like indexing (1-indexed) and default behavior (0=from beginning/to end). Since the schema has 0% description coverage, the description fully compensates by adding meaning beyond the schema's 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 identifies the action ('Read') and the resource ('stored context's content or a line range'). It is specific but does not explicitly differentiate from sibling tools like memcp_inspect_context or memcp_load_context, relying on the agent to infer distinctions from 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?

The description provides no guidance on when to use this tool versus its siblings. It does not mention prerequisites, alternatives, or when not to use it. The agent is left to infer use cases from the operation name and parameters.

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 only vaguely mentions connectivity and lacks specifics on read-only nature, authentication, rate limits, or how results are ordered.

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 and front-loaded: three lines of description followed by the parameter. 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 the simplicity (1 optional parameter, output schema exists), the description covers the needed semantics. It could mention output format specifics but is sufficient for basic 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?

The single parameter 'project' is explained with its default value and filtering behavior ('empty = all projects'), adding meaning beyond the schema which has 0% 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?

The description clearly states the tool retrieves graph statistics including node count, edge counts by type, and top entities. It distinguishes the tool's purpose from sibling tools, none of which explicitly deal with graph statistics.

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. Among siblings like memcp_search or memcp_related, there is no differentiation or contextual advice.

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 states it returns metadata and preview only, hinting at idempotent read. However, does not disclose error handling, auth, rate limits, or behavior for non-existent contexts, 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?

Very concise: one-sentence purpose, one-sentence usage guidance, and an Args section. No redundant information; front-loaded and efficient.

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 an existing output schema, the description covers purpose, usage, and parameter adequately. Assuming output schema documents return values, completeness is high.

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). The description adds minimal info: 'Context name to inspect'. Lacks format, constraints, or examples, but is adequate for a single string 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?

Description clearly specifies 'Inspect a stored context' with verb and resource, and distinguishes from siblings like 'memcp_get_context' by noting it provides metadata and preview without loading full content.

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?

Explicit guidance: 'Use this to check a context's type, size, and token count before deciding whether to load it into the prompt.' Implies when not to use (when full content needed), but no explicit alternatives named.

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 states 'List' which implies read-only, but does not disclose pagination, limits, or side effects. Additional behavioral context is missing.

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 with two sentences covering purpose and parameter. Front-loaded purpose. No wasted 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's simplicity (one optional parameter) and existence of an output schema (implied by context), the description is mostly adequate. However, it does not hint at the output structure, which could aid 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%, so the description compensates by explaining the 'project' parameter's purpose and default behavior ('empty = all projects'). This adds meaningful 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?

The description clearly states 'List all stored context variables,' providing a specific verb and resource. It distinguishes from siblings like memcp_get_context by implying it returns a collection, though not explicitly.

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., memcp_get_context, memcp_search). The description only mentions the project filter but lacks context for decision-making.

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 only states basic storage functionality without disclosing behavior such as overwrite policy, error handling, or storage limits. This minimal disclosure 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?

Description is short and front-loaded with the main purpose, followed by an Args section. Every sentence adds value, though the name mismatch could be clarified further.

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 4 parameters, no annotations, and an output schema (which covers return values), the description provides adequate usage details. However, it omits error conditions, return value meaning, and how this tool relates to retrieval tools like memcp_get_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?

Schema has 0% coverage, so description adds vital meaning: explains name format, content vs file_path exclusivity, and project's optionality. This goes well beyond the bare schema names, making parameter usage clear.

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 stores content as a named context variable on disk. It distinguishes from sibling tools by specifying its use for large content that should be accessible without loading into the prompt. However, the tool name 'load_context' might imply retrieval, which could cause confusion.

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?

Provides explicit guidance: 'Use this to save large content...' and advises on parameter exclusivity (content OR file_path). Lacks explicit when-not-to-use or alternative tools, but the context is clear enough for an AI agent to decide.

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 states 'Read' which implies non-destructive, but does not disclose behavior on invalid chunk_index, out-of-range start/end, or whether the context must be chunked. No mention of return format or error handling.

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: one-line purpose followed by parameter list. No fluff, front-loaded with the action. Every sentence provides necessary 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 tool is part of a chunking system, the description does not mention that the context must be chunked (likely via memcp_chunk_context) or what happens if chunk_index is out of bounds. Output schema exists but is not described; return values are not addressed. Missing optional behavior 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%, so description must compensate. The docstring provides brief descriptions for each parameter (context_name, chunk_index, start, end), and clarifies that start/end are 1-indexed with 0 meaning from beginning/end. This adds meaning beyond the schema titles, but descriptions are minimal.

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 'Read a specific chunk from a chunked context,' specifying the verb (Read) and the resource (specific chunk). This distinguishes it from siblings like memcp_get_context (reads entire context) and memcp_chunk_context (likely manages chunks).

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. The description does not mention when to use memcp_peek_chunk instead of memcp_get_context or memcp_filter_context, nor does it specify prerequisites like the context needing to be chunked first.

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 it returns status and memory stats, but does not mention side effects (likely none) or rate limits. Adequate for a simple ping.

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?

One sentence, zero waste. Every word is necessary and the description is 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 low complexity, empty schema, and presence of an output schema, the description is complete. No additional information about return values is needed.

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?

No parameters exist, and schema coverage is 100%. Baseline for 0 params is 4; description adds no extra meaning beyond the empty 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's a health check returning server status and memory statistics. The verb 'check' and resource 'server status' are explicit, and it is distinct from sibling tools which handle context and search.

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. It's implied for connectivity testing, but no explicit context or exclusions are 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 are provided, so the description carries the full burden. It states that the tool lists all projects with counts, but does not disclose any behavioral traits such as read-only nature, performance implications, or whether it requires authentication. The description is too minimal to be fully 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 consists of two concise sentences. The first sentence states the main action, and the second clarifies the inclusion criterion. Every word is purposeful; 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 tool's simplicity (no parameters, has output schema), the description is largely sufficient. It explains what the tool does and what it shows. However, it does not explain what 'insight/context/session counts' entail, but since an output schema exists, that detail may be covered there.

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 tool has zero parameters and schema coverage is trivially 100%. With no parameters to document, the baseline is 4. The description adds no parameter information, but none is needed.

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 'List', the resource 'projects', and the specific scope 'with insight/context/session counts'. It distinguishes from sibling tools like memcp_list_contexts and memcp_sessions by focusing on projects rather than contexts or sessions.

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. The description does not mention when not to use it or contrast with other tools, leaving the agent to infer usage from the name alone.

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 explains parameter behaviors well, especially max_tokens ('Token budget — returns results until budget is exhausted') and scope options. It does not mention read-only nature or side effects, but the retrieval semantics are implied. Overall, it adds useful behavioral context beyond the schema.

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: a single introductory sentence followed by a usage hint and a list of parameter explanations. Every sentence adds value, and the structure is front-loaded with the core purpose. No unnecessary words. This is exemplary 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 has an output schema, the description appropriately focuses on input parameters and usage. It covers the main use case, parameter filters, and the suggestion to call at session start. It does not discuss error handling or empty results, but with 8 parameters and an output schema, the description is sufficiently complete 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 0%, so the description must compensate. It provides explanations for all 8 parameters (e.g., query searches content, tags, and summary). This adds meaning beyond the schema titles. While it lacks examples or value ranges, it clearly defines each parameter's role, earning a 4.

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: 'Retrieve insights from memory.' It specifies the kind of content retrieved (decisions, preferences, technical findings) and distinguishes itself from siblings like memcp_remember (write) and memcp_search (likely a different search mode). The verb 'Retrieve' and resource 'insights' are specific, making it easy for an agent to understand what this tool 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 provides a clear usage hint: 'Call at session start to load relevant context.' This tells the agent when to use the tool. However, it does not explicitly mention when not to use it or suggest alternatives among siblings (e.g., memcp_search for different search needs). The context is clear but lacks exclusions, earning a 4.

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 the description carries the burden. It explains that helpful insights get a score boost and stronger edges, while misleading ones are penalized, and mentions closing the learning loop. However, it does not disclose potential side effects or requirements like authorization.

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 (3 lines plus Args) and front-loaded with the purpose. It could be slightly more structured but contains no fluff.

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 3 parameters and an output schema, the description adequately covers the tool's effect (score/edge changes) and parameter roles. It provides sufficient context 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?

Despite 0% schema description coverage, the description includes an 'Args' section that explains each parameter's meaning (e.g., 'helpful: True if the insight was helpful, False if misleading'), adding significant context beyond the schema's titles and defaults.

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 provides feedback on an insight, marking it as helpful or misleading, which distinguishes it from sibling tools that handle context management, search, and consolidation.

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 you want to reinforce an insight) but does not explicitly state when not to use it or suggest alternatives, leaving some ambiguity about appropriate 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?

With no annotations provided, the description carries full burden. It describes the traversal operation and edge types but omits specific behavioral details like whether the tool is read-only, error handling for missing insight_id, or performance characteristics.

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 with a front-loaded lead sentence, followed by a brief explanation of what the tool does, then parameter details. No extraneous 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 tool's graph traversal complexity and an existing output schema, the description adequately covers the main behavior. However, it could mention the expected output format or common error conditions for completeness.

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 coverage is 0%, but the Arg descriptions add meaning: insight_id is the start point, edge_type filters by type (with allowed values listed), and depth specifies hops. This compensates for the schema's lack of property 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 traverses a graph from an insight to find connected knowledge, specifying relationship types like semantic similarity, temporal proximity, causal chains, or shared entities. This distinguishes it from sibling tools like memcp_search and memcp_recall.

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 wanting to explore graph connections from a given insight, but lacks explicit guidance on when to use this tool versus alternatives like memcp_search or memcp_peek_chunk, and does not provide 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 the full burden. It explains the basic action (save to persistent memory) but lacks details on idempotency, overwrite behavior, limits, or return values. The presence of an output schema mitigates this slightly, but the description itself could be more 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 well-structured with a clear lead sentence, a usage paragraph, and parameter documentation. It is front-loaded, though the Args section is somewhat lengthy. Every sentence adds value, but slight trimming could improve 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 8 parameters, 1 required, and no annotations, the description covers purpose, usage guidelines, and parameter semantics thoroughly. It does not explain return values, but the output schema likely handles that. The tool's complexity is moderate, and the description provides sufficient 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?

With 0% schema description coverage, the description fully compensates by explaining each parameter in the Args section. It adds context: 'be concise but complete' for content, enumeration of categories, description of importance levels, and format guidance for tags and entities. This is highly valuable 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 'Save an important insight to persistent memory' with a specific verb and resource. It distinguishes itself from sibling tools like memcp_recall (retrieval) and memcp_search, establishing its unique role as the write operation.

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 when to use: 'remember key decisions, facts, user preferences, or technical findings that should be preserved across conversations.' However, it does not explicitly state when not to use or mention alternatives, though the context of siblings implies read tools for retrieval.

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 discloses decompression and re-insertion behavior. It does not cover permissions, conflicts, or error cases, which limits 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?

The description is concise with a clear front-loaded purpose, followed by brief implementation details and parameter explanations. 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 the presence of an output schema, the description covers the core functionality adequately. It could mention error handling or prerequisites (e.g., item must be archived), but overall it is sufficiently complete for a two-parameter 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?

The description adds meaning to both parameters beyond the bare schema: 'name' is identified as context name or insight ID, and 'item_type' explains the allowed values and 'auto' behavior. This compensates for the 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?

The description clearly states it restores archived contexts or insights, using specific verbs and resources. It differentiates from sibling tools like memcp_forget or memcp_recall that handle other 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?

The description specifies the tool is for restoring archived items, providing clear context. However, it lacks explicit guidance on when not to use it or alternatives for non-archived items.

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?

In the absence of annotations, the description discloses that no changes are made, describes candidate criteria (stale, low-access, past retention) and immunity conditions (high importance, frequent access, protected tags). It does not mention authentication or rate limits, but captures key 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?

The description is two sentences plus a parameter list, front-loading the core purpose and behavior. Every sentence adds value without redundancy or excess.

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 (dry-run preview, two parameters), the description covers purpose, behavior, and parameter semantics. An output schema exists, so return format explanation is not required. It lacks explicit sibling differentiation but is otherwise 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?

The schema has 0% parameter descriptions, so the description compensates by explaining 'archive_days' and 'purge_days' with their purpose and defaults. However, it states defaults from env (30, 180 days) while schema shows default 0, creating potential confusion.

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 is a dry-run preview for archiving and purging, with explicit verb 'Preview' and resource 'retention'. It distinguishes from the sibling 'memcp_retention_run' which actually executes the action, by stating 'no changes made'.

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 safe usage via 'dry-run, no changes made' but does not explicitly mention when to use this tool versus alternatives like 'memcp_retention_run'. The guidance is implicit rather than direct.

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 properly discloses that archiving compresses and moves stale items, while purging permanently deletes archived items past a threshold and logs metadata for audit. This provides key behavioral details beyond the bare operation.

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 and well-structured, with a brief overview paragraph and a clear Args list. Every sentence adds value, and there is no extraneous 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 tool has an output schema (not shown), the description adequately covers the actions, parameters, and outcomes. It could mention the retention period source or order of operations, but overall it is sufficiently complete for a simple boolean-parameter 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 coverage is 0%, so the description compensates by explaining both parameters: archive defaults to true and 'Archive eligible items', purge defaults to false and 'Purge archived items past retention period'. This adds meaning beyond the schema's property 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 tool executes retention actions (archive and purge) and describes the effects. It distinguishes from siblings like memcp_retention_preview by indicating it actually runs the actions, though this differentiation is implicit rather than 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?

No guidance is provided on when to use this tool versus alternatives like memcp_retention_preview. There is no mention of prerequisites, recommended order of operations, or contexts where running retention is appropriate vs. not.

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 mentions auto-selection of search method (BM25 > keyword) but lacks disclosure of other behavioral traits such as idempotency, rate limits, or side effects. With no annotations, the description carries full burden and provides 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?

The description is concise and front-loaded with the core purpose. It uses bullet points for parameters and includes an optional installation note. Every sentence contributes value without being overly 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 the complexity of 6 parameters and the presence of an output schema, the description covers the tool's purpose, parameters, and behavioral auto-selection. It adequately explains the source and scope options, though could elaborate on what 'memory insights' and 'context chunks' are if not obvious from 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 description includes an Args section that explains each parameter (query, limit, source, max_tokens, project, scope) with defaults and allowed values, adding significant meaning beyond the input schema which only has types and defaults. This fully compensates for the 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?

The description clearly states 'Search across memory insights and context chunks,' specifying the verb (search) and the resources (memory insights, context chunks). Among sibling tools like memcp_recall and memcp_related, this tool is distinct as a general search across multiple sources.

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 searching across memories and contexts but does not explicitly state when to use this tool versus alternatives like memcp_recall or memcp_related. No when-not or alternative guidance is 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 are provided, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. For a listing tool, it is reasonable to assume it is read-only, but this is not explicitly stated.

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 with two lines for the main action and two parameter explanations. It is front-loaded with the purpose. Slightly more structure could be added, but overall it is efficient.

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 simplicity of the tool (2 parameters, list operation), the description is minimally adequate. However, it lacks details on pagination, sorting, or the return format, which an agent might need. An output schema exists but its content is not described.

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 description coverage is 0%, and the description adds value by explaining that 'project' filters by project (empty = all) and 'limit' is the max sessions to return (default 20). This compensates for the lack of schema 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 action ('List') and the resource ('sessions'), and specifies optional filtering by project. This distinguishes it from sibling tools like memcp_list_contexts and memcp_projects, which deal with different resources.

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 given on when to use this tool versus alternatives (e.g., memcp_search or memcp_recall). The description only lists the parameters without any context for 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?

No annotations are provided, so the description carries full burden. It implies a read-only operation ('statistics') but does not explicitly confirm non-destructive nature, authentication needs, or side effects. Lacks details on rate limits or error conditions.

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, front-loaded with purpose and output. No redundant information. Efficiently structured for quick reading.

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?

Output schema exists, so return value details are not needed. However, given zero annotations and many sibling tools, the description could provide more context on the scope of statistics (global vs per project/session) and how to interpret importance distribution. It is 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 coverage is 0%, so description must add meaning. It states parameters filter by 'project' and 'session', which adds basic context. However, it does not specify format or behavior (e.g., case sensitivity, wildcards). Provides minimal enhancement 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 it provides 'memory statistics' and lists specific metrics: insight count, categories, importance distribution. This distinguishes it from sibling tools like memcp_graph_stats (likely graph-specific) and memcp_recall (retrieval).

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 mentions optional filters (project, session) but provides no guidance on when to use this tool versus alternatives like memcp_graph_stats or memcp_ping. No exclusions or context-specific usage tips.

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