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

No annotations are provided, so the description must fully disclose behavioral traits. It indicates a read-only analytics operation and hints at output structure (hit rate, etc.), but does not mention potential costs, rate limits, refresh behavior, or required permissions. The description is adequate but leaves some behavioral aspects unspecified.

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 paragraphs long, with a brief introductory sentence and a bulleted list of metrics. It is mostly concise, though the list could be integrated more tightly. Overall, it is well-structured and front-loads the key 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 that the tool has no input parameters and an output schema exists, the description sufficiently covers its purpose and what analytics it provides. It explains the kind of insights available (cache performance, network effects) and how to use it, leaving no critical gaps for an agent to invoke 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?

The input schema has zero parameters, so schema description coverage is trivially 100%. With no parameters, the description does not need to add parameter semantics, and the baseline score of 4 applies. The description appropriately focuses on the tool's output and purpose.

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

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

The description clearly states that the tool provides 'Detailed analytics about cache usage, trust, and network effects' and lists specific metrics like hit rate, most accessed entries, etc. This distinguishes it from sibling tools such as cache_stats (likely simpler stats) and cache_list (entry listing), making the purpose unmistakable.

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 says 'Use this to understand how the shared cache is performing and how strong the network effect has become,' which gives context but does not explicitly state when to use this tool versus alternatives like cache_search or cache_stats. No when-not-to-use guidance or mention of alternative tools 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, so the description bears full responsibility for behavioral disclosure. It mentions listing entries and filtering by tags but does not explicitly state that the operation is read-only, side-effect free, or require any permissions. This leaves behavioral traits opaque.

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 short paragraphs. The first sentence front-loads the core purpose. No redundant or filler language. Docstring format is clean and scannable.

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 an output schema present, return value details are not strictly needed. However, the description only mentions 'trust scores' without listing other likely fields (e.g., key, value, timestamp). Given two optional parameters and no annotations, the description is adequate but not thorough.

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?

Input schema properties lack descriptions (0% coverage). The description compensates by explaining 'limit: Max entries to return (default: 20, max: 100)' and 'tags: Filter by tags, comma-separated (e.g. 'weather,temperature')'. This adds range and format constraints beyond the schema.

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

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

Description clearly states 'List available cache entries with trust scores', indicating a specific verb and resource. It briefly explains the purpose 'Browse what other agents have cached', but does not explicitly differentiate from sibling tools like cache_lookup or cache_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?

The description implies use for browsing cached entries but provides no guidance on when not to use or alternatives. With siblings like cache_lookup and cache_search, explicit differentiation would help an agent choose correctly.

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 it returns a value with a trust score and explains the trust_score meaning. However, it does not describe behavior when the key is not found (e.g., returns null or error). This is a minor gap for a lookup 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 well-structured and concise: a short intro sentence, followed by usage guidance, trust score elaboration, and parameter docs with examples. No extraneous information, and front-loaded with the core 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 the tool's simplicity (2 parameters, lookup only), the description covers input, usage context, and return value aspects. It distinguishes from siblings. However, it could mention the outcome when the key is missing, and the output schema exists but is not referenced. Still, it is largely 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%, but the description fully compensates by explaining both parameters: 'key' with example patterns like 'weather:berlin:2026-03-28', and 'agent_id' as an analytics identifier. This adds significant meaning 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: 'Look up a cached result by key. Returns the stored value if found, with trust score.' It specifies the resource (cache) and the verb (look up), and differentiates from sibling tools like cache_store and cache_list.

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

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

Provides explicit guidance: 'Use this BEFORE computing expensive results' and explains the benefit of saving tokens and latency. It also clarifies that another agent may have cached the result. No explicit exclusion of when not to use, but the guidance is strong.

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 cover behavioral aspects. It mentions that results include trust scores, but does not disclose if the search is read-only, any side effects, or performance characteristics. This leaves some gaps.

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

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

The description is concise, with the purpose and guideline in the first two lines, followed by a structured 'Args' section. 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?

The description covers purpose, parameters, and usage guideline adequately. With an output schema present, it does not need to detail return values, but it could mention ordering or pagination 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?

Schema description coverage is 0%, but the description compensates fully with an 'Args' section that explains the 'query' parameter with examples and the 'limit' parameter with default and max values, adding meaning beyond the schema's type information.

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 'Search' and the resource 'shared cache', specifying that it finds relevant cached results from other agents. This distinguishes it from siblings like cache_list or cache_lookup, which likely do not perform keyword 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?

The description advises using this tool before computing to reuse cached results, providing a clear when-to-use context. However, it does not explicitly mention when not to use it or compare to alternatives like cache_lookup for specific keys.

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 burden. It indicates a read operation (get stats) but does not mention any potential side effects, permissions, or rate limits. However, the tool is simple and harmless, so a minimal disclosure is acceptable.

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

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

The description is very concise with two sentences: the first states the purpose, the second provides an alternative. 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 no parameters and an existing output schema, the description is complete. It covers what the tool does and when to use a different tool, requiring no further elaboration.

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 0 parameters, and the schema coverage is 100%. The description does not need to add parameter information, meeting the baseline for zero-parameter tools.

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 'Get' and the resource 'shared cache', listing specific outputs (hits, misses, top queries). It distinguishes from the sibling cache_analytics, fulfilling the need for specificity and differentiation.

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

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

The description explicitly tells when not to use this tool and directs to an alternative: 'For more detailed analytics including trust scores and network effects, use cache_analytics instead.' This provides clear 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?

With no annotations, the description carries full burden. It explains trust_score initialization, ttl behavior, and that other agents can increase trust. It lacks disclosure on any potential side effects, but caching is generally benign.

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 purpose statement, usage guidance, and a labeled Args section. It is slightly verbose but every sentence adds value.

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

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

Given the tool's complexity (5 parameters, output schema exists), the description covers purpose, when to use, parameter details, and behavioral notes. It is self-contained and leaves no major 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 coverage is 0%, so description must compensate. It provides detailed explanations for all 5 parameters including examples for key, accepted formats for value, default and max for ttl_seconds, comma-separated for tags, and attribution for agent_id.

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: 'Store a computed result in the shared cache so other agents can reuse it.' It distinguishes from sibling tools like cache_lookup and cache_search by specifying the action of storing.

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 when to use: 'After computing an expensive result...' and mentions related tools (confirm_entry). However, it does not explicitly state when not to use.

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

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

With no annotations provided, the description carries the full burden of behavioral transparency. It discloses that each agent can confirm an entry once, duplicates are ignored, and trust scores increase. It does not cover potential side effects or failure modes, but the core behaviors are well explained.

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

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

The description is well-structured: it starts with a clear primary action statement, then explains the benefit and behavior, and finally lists arguments with examples. Every sentence adds value without unnecessary 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 context includes an output schema, the description does not need to explain return values. It covers the tool's purpose, behavior, and parameters sufficiently for a simple confirmation action. The description is complete for its 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 coverage is 0%, so the description must explain parameters. It does so effectively, providing a clear example for 'key' (e.g., 'weather:berlin:2026-03-28') and explaining that 'agent_id' defaults to 'mcp-agent'. 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 that the tool confirms a cached result and increases trust score, with a specific verb ('confirm') and resource ('cached result'). It distinguishes itself from sibling tools like cache_store, cache_list, etc., by focusing on verification and trust building.

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 when to use the tool: 'when you use a cached result and verify it's correct, confirm it.' It also notes that duplicate confirmations are ignored and highlights the network effect. However, it does not explicitly state when not to use it or provide alternative tools for other scenarios.

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

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

No annotations are provided, so the description carries full burden. It discloses that entries are filtered by min_trust and sorted by trust_score, implying a read-only operation. It does not discuss performance, errors, or edge cases like empty results, but the core behavior is covered.

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), front-loaded with purpose, and uses a clear Args section. 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 an output schema exists (not shown), the description need not detail return format. It covers input parameters, filtering logic, and sorting. It could optionally mention that results are a list of entries, but the information is sufficient for an AI agent.

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), so the description must compensate. It explains min_trust as 'Minimum trust score required (default: 3 = confirmed by 3+ agents)' and limit as 'Max entries to return (default: 20)', adding clear semantics beyond the schema's type and 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 tool gets cache entries confirmed by multiple agents (high trust). It distinguishes from siblings like cache_list (all entries) and cache_search by specifying the filtering condition. The verb 'Get' and resource 'cache entries (high trust)' are specific.

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 'Use this to find the most trustworthy precomputed results available.' This provides clear context for when to use the tool. However, it does not explicitly exclude other cases or mention sibling alternatives, which would earn a 5.

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