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

No annotations provided, so description carries full burden. 'Track' implies persistence but does not disclose side effects, idempotency, lifecycle workflow implications, or what success/failure looks like for this 7-parameter mutation tool.

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

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

Single sentence with efficient structure. Front-loaded with verb. Every word earns place, though extreme brevity may contribute to insufficient behavioral disclosure for a complex mutation tool.

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?

Insufficient for a 7-parameter mutation tool with enum-based workflow state (status field) and no output schema. Missing: relationship to 'find_bounties' workflow, persistence guarantees, and return value description.

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

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

Schema coverage is 86% (high), establishing baseline 3. The parenthetical list '(bounty, grant...)' maps to enum values in the schema, adding marginal real-world context, but no parameter syntax or semantic relationships are explained beyond the schema itself.

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 uses a specific verb ('Track') and resource ('revenue opportunity'), and the parenthetical examples clarify scope. It implicitly distinguishes from sibling 'update_revenue_status' (add vs update), though 'Track' is slightly less precise than 'Create' or 'Add' for a mutation 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?

No guidance provided on when to use this tool versus siblings like 'find_bounties' (discovery) or 'update_revenue_status' (modification). Does not mention workflow prerequisites or 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 disclosure but fails to clarify critical aspects: whether reading consumes/removes messages from the inbox (pop vs peek), authentication requirements, or rate limits. 'Read' implies read-only but lacks necessary operational 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 extremely efficient at 6 words with no filler content and is front-loaded with the action. However, given the complete absence of annotations, it may be inappropriately brief rather than appropriately concise, warranting a 4 instead of 5.

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

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

For a tool with no annotations, no output schema, and undefined message lifecycle behavior (consumed vs retained), the single-sentence description is inadequate. It fails to explain what 'pending' means or what the return format looks like.

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 'agent' parameter fully documented as 'Agent name to check inbox for'. The description adds no additional parameter semantics, but baseline 3 is appropriate when the schema already provides complete documentation.

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 provides a specific verb ('Read') and resource ('pending messages'), clearly indicating this is an inbox retrieval tool. While it effectively distinguishes itself from revenue/crypto siblings implicitly, it lacks explicit differentiation from 'agent_message' (which likely sends messages), preventing a score of 5.

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

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

No guidance provided on when to use this tool versus alternatives like 'agent_message', or prerequisites such as agent existence verification. The description states what the tool does but not when an agent should select it over sibling tools.

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

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

With no annotations provided, the description carries full responsibility for behavioral disclosure, but fails to specify delivery guarantees, persistence duration, what triggers agent notification, or failure modes. The 'Honest communication only' statement is vague and does not describe actual tool behavior, side effects, or state changes.

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 (two sentences) and front-loaded with the functional purpose, which is efficient. However, the second sentence ('Honest communication only.') consumes space without providing actionable guidance for an AI agent, functioning as noise rather than signal.

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 a related sibling tool (agent_inbox) and five parameters with multiple enums, the description lacks necessary context. It omits the relationship between sending and receiving workflows, provides no guidance on the parameter taxonomy, and offers no details about return values or success confirmation despite having no output schema.

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 60% (moderate), leaving the semantic meaning of the 'type' and 'priority' enums unexplained in the schema. The description offers no compensation for this gap—it does not clarify when to use 'critical' vs 'high' priority or what distinguishes a 'task' from a 'request', leaving significant parameter value guidance uncovered.

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 provides a clear verb ('Send/receive'), resource ('messages'), and scope ('between AI agents for coordination'). It effectively distinguishes from non-communication siblings like 'crypto_portfolio' or 'check_prs'. However, the overlap with sibling 'agent_inbox' is unresolved, and the 'Honest communication only' clause adds no functional clarity.

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

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

There is no guidance on when to use this tool versus the similar 'agent_inbox' sibling, nor does it specify when to broadcast ('ALL') versus direct message, or when to use specific message types like 'alert' versus 'task'. No prerequisites or error conditions 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 provided, so description carries full disclosure burden. It mentions the revenue-tracking purpose but fails to disclose side effects, return format/pagination, authentication requirements, or what criteria determine 'might earn money'.

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 tight single sentence structure. Front-loaded with action ('Check status'), followed by scope and purpose ('track which ones might earn money'). No redundant words or repetition of structured metadata.

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?

Adequate for a zero-parameter tool but gaps remain. Given no output schema, the description should hint at return structure (list? count?). The 'across repos' scope mechanism is unexplained, though the revenue connection to sibling tools is appropriately noted.

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?

Zero parameters with 100% schema coverage (vacuously true). With no parameters to describe, this meets the baseline score of 4 as defined in the evaluation rules.

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?

Clear verb ('Check') + resource ('open PRs') + scope ('across repos') and distinguishes from bounty-focused siblings by mentioning the PR context. However, 'across repos' is ambiguous given zero parameters (which repos?), and 'Check status' is slightly generic.

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

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

No explicit guidance on when to use versus alternatives like 'find_bounties' or 'scan_bounty'. The phrase 'track which ones might earn money' implies revenue-tracking use case but doesn't state prerequisites or when to prefer this over other revenue tools.

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

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

No annotations provided, so description carries full burden. Mentions 'real-time' and external source 'CoinGecko' but omits critical behavioral details: authentication requirements, rate limits, error handling for API failures, data freshness guarantees, or response format structure.

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

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

Single sentence, front-loaded with key information. Minor deduction for the parenthetical '(no fake numbers)' which consumes space without conveying technical constraints or behavior.

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?

Tool has low complexity (1 optional parameter) but no output schema or annotations. Description identifies the data source but fails to describe return value structure, format, or error conditions. Adequate but gaps remain for integration reliability.

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% (the 'coins' parameter is fully documented with type, format, and defaults). Description adds no parameter-specific guidance, but baseline 3 is appropriate when schema documentation is complete.

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?

States specific verb (Get) and resource (crypto portfolio value) with clear source (CoinGecko). Distinguishes effectively from business-oriented siblings (revenue, bounties, PR tools). Minor deduction for the informal parenthetical '(no fake numbers)' which adds no technical clarity.

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

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

Provides no guidance on when to use this tool versus alternatives, nor any prerequisites (e.g., CoinGecko API availability, rate limit considerations). The agent must infer applicability from the tool 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 provided, so description carries full burden. It successfully discloses the 'scam filtering' behavior, which is a critical value-add. However, it omits auth requirements, rate limits, pagination behavior, or return format disclosure that would be expected for a zero-annotation search 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?

Two sentences, zero waste. Front-loaded with the core action ('Search GitHub...'), followed immediately by the key differentiator ('Filters out known scams'). No redundant phrases or filler text.

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?

Good completion for a 2-parameter tool with 100% schema coverage. The description establishes domain (GitHub) and quality guarantees (scam filtering). Minor gap: missing description of return values since no output schema exists (what fields returned? how many results?).

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

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

Schema description coverage is 100% (both parameters fully documented in schema), establishing baseline 3. The description adds domain context ('GitHub') which helps interpret the query parameter, but does not elaborate on query syntax, validation rules, or the significance of the min_stars threshold beyond the schema definitions.

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?

Excellent clarity: 'Search GitHub for real, paying bounty opportunities' provides specific verb (search), specific resource (GitHub bounties), and quality qualifier (real, paying). The 'Filters out known scams' clause distinguishes this from siblings like 'scan_bounty' by implying a curated/filtered search rather than a raw scan.

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 'Filters out known scams' implies usage context (use when seeking trustworthy opportunities), but lacks explicit when-to-use guidance versus siblings like 'scan_bounty' or 'check_prs'. No explicit alternatives or prerequisites 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?

Implies read-only operation via 'List' and indicates unfiltered scope with 'all', which partially compensates for missing annotations. However, fails to disclose return format, pagination behavior, or authentication requirements given zero annotation coverage.

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

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

Single front-loaded sentence with zero waste. Begins with action verb and efficiently communicates both the resource and the specific data attribute returned.

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?

Adequate for a zero-parameter tool but falls short given lack of output schema and annotations. Description omits return value structure, pagination limits, and cache behavior necessary for agent planning.

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 contains zero parameters, warranting baseline score per guidelines. Description correctly implies no filtering capabilities are available by stating 'all products', aligning with 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?

States specific verb 'List' and resource 'products' plus specific attribute 'monetization status'. Implies distinction from sibling 'revenue_dashboard' (aggregation vs catalog) and 'update_revenue_status' (read vs write), though does not explicitly name alternatives.

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 no guidance on when to use this versus siblings like 'revenue_dashboard' or 'find_bounties'. Lacks prerequisites, scoping constraints, or exclusion criteria.

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 fully disclose behavioral traits. It mentions 'Get' implying a read operation, but does not explicitly confirm safety, idempotency, or side effects. The phrase 'Honest numbers only' hints at some filtering logic (perhaps excluding pipeline estimates or unverified entries) but remains cryptic and unexplained. No information on rate limits, authentication requirements, or response format is provided.

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 appropriately brief with two distinct phrases. However, 'Honest numbers only' consumes space without adding actionable clarity—it reads as vague flavor text rather than functional documentation. The first clause efficiently describes scope (full dashboard, entries, totals, pipeline).

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 zero parameters and no output schema, the description adequately lists the components retrieved (entries, totals, pipeline status). However, for a dashboard tool, it should clarify whether it returns raw data or aggregated summaries, and what 'pipeline status' encompasses (e.g., stages, probabilities). The coverage is minimal but sufficient given the schema simplicity.

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 accepts zero parameters. According to scoring guidelines, zero-parameter tools receive a baseline score of 4. The description does not need to compensate for missing parameter documentation since the schema is self-explanatory (empty object).

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 resource (revenue dashboard) along with scope (all entries, totals, pipeline status). However, it inadequately distinguishes from siblings like 'weekly_report' or 'crypto_portfolio' which might also contain revenue data. The 'Honest numbers only' qualifier does not clarify functional purpose.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., authentication, date ranges) or indicate when to prefer 'update_revenue_status' or 'add_revenue_entry' instead. The phrase 'Honest numbers only' hints at a filter criterion but fails to guide selection logic.

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. It discloses the output format (0-5 score) and character of the check ('Anti-scam'), but lacks operational details like error conditions, rate limits, or what specific legitimacy criteria are evaluated.

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?

Perfectly sized at one impactful sentence with zero waste. The em-dash structure front-loads the tool type ('Anti-scam scanner') immediately, followed by the specific action and output format.

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 single-parameter tool without output schema, the description is nearly complete by specifying the scoring range. Minor gaps remain regarding error handling for invalid repos, but the core functionality is adequately covered.

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 ('GitHub owner/repo'), the description doesn't need to add significant parameter semantics. It confirms the context ('GitHub repo') but doesn't expand on syntax or validation rules beyond the schema, warranting the baseline score.

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 uses specific verbs ('checks') and resources ('GitHub repo's bounty') and clearly distinguishes itself from sibling 'find_bounties' by specifying its 'Anti-scam' nature and unique 0-5 scoring output format.

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?

While 'Anti-scam scanner' implies a verification use case, there is no explicit guidance on when to invoke this versus alternatives like 'find_bounties' or 'check_prs', nor any mention of prerequisites or exclusions.

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

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

No annotations provided, so description carries full disclosure burden. While it hints at state machine behavior via the example, it fails to mention side effects, validation rules for state transitions, notifications triggered, or error conditions for invalid updates.

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

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

Single efficient sentence with parenthetical example. Front-loaded purpose with zero waste. Appropriate density though brevity limits behavioral disclosure given lack of annotations.

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?

Mutation tool with zero annotations, no output schema, and only basic state workflow description. Lacks critical safety context: valid transition rules, permissions required, irreversibility warnings, or failure modes expected for financial data operations.

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 67% (id and notes described). The description implicitly documents valid status values through the workflow example, adding semantic context beyond raw schema, but doesn't explicitly map parameter meanings or transition constraints.

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?

Clear verb (Update) and resource (revenue entry status) with concrete state workflow example (pending → submitted → paid). Doesn't explicitly distinguish from sibling `add_revenue_entry` (create vs update).

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 state transition example implies workflow progression, providing implicit usage context. However, no explicit guidance on when to use vs `add_revenue_entry`, prerequisites, or invalid transition handling.

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, description carries full burden. It adds valuable behavioral context that only 'verified data' is returned (not projections/unconfirmed entries), but lacks disclosure on return format, failure behavior, or side effects.

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

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

Extremely concise single sentence with em-dash separation. Every word earns its place; 'honest' and 'verified' modify behavior while 'weekly' scopes the temporal range.

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?

Adequate for a zero-parameter tool, but gaps remain: no output format description (PDF? JSON? text?), no mention of date range mechanics (current week? previous?), and no failure mode documentation.

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

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

Zero parameters present, establishing baseline 4. No parameters requiring semantic clarification exist.

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?

Clear verb 'Generate' and resource 'weekly revenue report'. The 'honest' and 'verified data' qualifiers help distinguish from potentially unfiltered siblings like revenue_dashboard, though explicit differentiation is absent.

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

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

No explicit guidance on when to use this versus revenue_dashboard or add_revenue_entry. No prerequisites or conditions mentioned.

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