Setlist Fm

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds no behavioral context beyond what annotations provide, which is adequate but not enhanced.

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 (3 words) with no wasted words, but it sacrifices substance. While front-loaded and efficient, it does not earn its place by providing enough 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?

For a simple lookup tool with no output schema, the description is incomplete. It does not specify what data is returned (e.g., artist metadata) or any usage constraints. The agent is left guessing about the output format.

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 one parameter 'mbid' with 0% coverage (no description). The description only says 'by MBID', implying the parameter is an identifier but does not explain its format, required format, or example values. With low schema coverage, the description fails to fully compensate.

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 'Artist by MBID' clearly indicates the tool retrieves an artist given a MusicBrainz ID. It distinguishes from siblings like artist_search (search by name) and artist_setlists (get setlists). However, it could be more explicit about the action (e.g., 'Get artist details').

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

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

No guidance on when to use this tool versus alternatives like artist_search. The description does not mention when to prefer this over other artist-related tools, leaving the agent to infer usage from the name.

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds no behavioral context beyond this, such as pagination, result format, or search semantics. With annotations, the bar is lower but the description still contributes nothing extra.

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

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

The description is a single sentence, but it is under-specified rather than concise. It lacks important details, making it insufficient for an agent to understand the tool's usage.

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 5 parameters, no output schema, and 0% schema coverage, the description is completely inadequate. It should provide more context about the search functionality, return behavior, and parameter usage.

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

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

Schema description coverage is 0% and the description does not explain any of the 5 parameters (p, sort, artistMbid, artistName, artistTmid). There is no guidance on how to use them effectively, so the description fails to compensate for the lack of schema 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 'Search artists.' indicates a verb+resource, but is vague about what kind of search it performs and does not distinguish from sibling tools like 'artist' or 'artist_setlists'. It is better than a tautology but lacks specificity.

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 'artist' (single lookup) or 'artist_setlists' (setlists). No context about appropriate scenarios 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is clear. However, the description adds no behavioral details beyond the annotations, such as pagination, limits, or data volume, which would be helpful given the openWorldHint.

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 short (two words) but lacks substance. Conciseness is efficient communication; here it is under-specified, not concise. More information could be added without losing brevity.

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

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

Given the tool has 2 parameters, no output schema, and annotations, the description is severely incomplete. It does not explain the return format, parameter meanings, or any behavior. It fails to provide a complete understanding 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 description coverage is 0%, and the description does not explain the parameters 'p' or 'mbid'. 'mbid' is required and likely an artist identifier, but no clarification is given. The description fails to add value beyond the raw 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 'Artist's setlists' indicates the tool returns setlists for an artist, which is distinguishable from siblings like 'artist' or 'setlist'. However, it lacks a verb and does not specify what exactly it returns (list of setlists, details?). It's minimal but not a tautology.

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

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

No guidance on when to use this tool versus alternatives like 'setlist_search' or 'artist'. No prerequisites or conditions mentioned. The description provides no usage context.

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

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false. Description adds that it routes to underlying tools and returns structured answers with citations, which is additional but not critical beyond annotations.

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

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

Description is somewhat lengthy but each sentence adds value. It is front-loaded with the key preference statement. Could be slightly more concise but still effective.

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 (router to 2,520 tools), description covers what it does, when to use, and provides examples. No output schema, but output format is described as structured answers with citations.

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 one parameter. Description adds meaning by specifying appropriate question types and examples, going beyond the schema's generic 'Your question or request in natural language'.

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

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

Description clearly states the tool is preferred over web search for factual questions about structured data, listing specific domains and examples. It distinguishes itself from siblings by being the primary question-answering router.

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

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

Explicitly says 'PREFER OVER WEB SEARCH' and gives when-to-use criteria (e.g., 'what is', 'look up'). Provides examples. Does not explicitly mention when not to use, but context is clear.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral details: it resolves the market, classifies the bet, fans out to relevant packs (e.g., crypto+fred+gdelt for BTC), and returns an evidence packet and market-vs-model comparison—none contradicting annotations.

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

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

The description is four sentences, front-loaded with the action and purpose. Every sentence adds value—no wasted words. It is dense but clear, covering functionality, alternatives, and use cases efficiently.

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

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

No output schema exists, but the description explains the return value: 'evidence packet plus simple market-vs-model comparison'. It also outlines the processing steps (resolve, classify, fan out). For a complex tool, this is sufficiently 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 coverage is 100%. The description adds meaning: explains 'market' accepts slug, URL, or question text; and 'depth' with 'quick = 2-3 sources, thorough = full fan-out, default thorough'. This enriches the enum and descriptions in the schema.

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

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

The description clearly states the tool researches Polymarket bets by pulling Pipeworx data. It specifies the verb 'research' and the resource 'Polymarket bet', and distinguishes itself from siblings like polymarket_arbitrage and polymarket_edges by being the core research tool.

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

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

The description provides explicit use cases: 'should I bet on X?', 'what does the data say about this Polymarket market?', and 'is there edge in this bet?'. It also contrasts with siblings by noting that agents using this tool convert better than those discovering packs themselves.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds no behavioral context beyond 'search', which is already implied by the name.

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?

While extremely short, the description is under-specified rather than concise. It omits critical information needed for effective use.

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

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

With no output schema, 0% parameter coverage, and three parameters, the description is grossly incomplete. The agent cannot infer how to invoke the tool correctly.

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

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

Schema description coverage is 0%, so the description must compensate, but it does not mention any of the three parameters (p, name, country). The agent gets no clue about parameter meanings.

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

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

The description 'City search' is essentially a tautology of the tool name 'cities'. It provides minimal differentiation from sibling tools like 'countries' or 'venue_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 is given on when to use this tool versus alternatives. The description lacks any context about intended use cases.

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?

Annotations already mark it as readOnlyHint=true and destructiveHint=false. The description adds behavioral context: it pulls financial metrics for companies and adverse event counts/approvals/trials for drugs, returns paired data with citation URIs, and replaces 8-15 agent calls. No contradictions; description complements annotations well.

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 informative but slightly verbose. It front-loads the core purpose and uses bullet-like structure for types. A few redundancies (e.g., listing example phrases twice) could be trimmed, but overall it is well-organized 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?

Given no output schema, the description explains return format as 'paired data + pipeworx:// citation URIs' and lists specific data points for each type. It covers essential inputs and outputs, though a bit more detail on the output structure (e.g., table format) would improve completeness. Still 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 100%, but the description adds significant meaning: for type='company', it lists specific metrics (revenue, net income, cash, long-term debt); for type='drug', it lists report counts, approvals, trial counts. This goes beyond the enum descriptions in the schema, making parameters clear and actionable.

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 compares 2-5 companies or drugs side by side, specifying data sources (SEC EDGAR/XBRL for companies; FAERS, FDA, clinical trials for drugs). It distinguishes from siblings like entity_profile by explicitly noting it replaces multiple sequential calls, making its purpose unique and 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 provides explicit usage triggers (e.g., 'compare X and Y', 'X vs Y', 'stack up', 'which is bigger') and expected output (tables/rankings). While it does not explicitly list when not to use it, the context implies single-entity queries should use entity_profile, a sibling tool. Clear context with minor omission of negative 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?

Annotations already indicate readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds no behavioral insights beyond what is already in the annotations, such as data freshness or pagination.

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, consisting of two words. It is front-loaded and contains no fluff, though it could be slightly more descriptive (e.g., 'Returns a list of all countries').

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

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

The tool has no output schema, so the description should explain the return value (e.g., names, codes, format). It only says 'Country list,' which is insufficient for an agent to understand the output structure.

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 coverage is inherently 100%. The description does not need to explain parameters. Baseline for zero parameters is 4, and the description satisfies this.

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 'Country list.' identifies the resource (countries) and implies a retrieval operation, but it lacks a verb and does not differentiate from sibling tools like 'cities' or 'artist'. It is minimal but not misleading.

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. There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds that it returns top-N relevant tools with names+descriptions, and lists example domains. Provides context beyond annotations but does not detail ordering or ranking algorithm.

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?

Front-loaded with purpose, then usage guidance, examples, and return value. Every sentence adds value; no fluff. Efficient and well-structured.

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 output schema, two parameters with full coverage), the description fully equips an agent: states what it does, when to call, examples, and that it returns names+descriptions. No 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 100% with clear descriptions. The tool description adds context by listing example domains that can be used in queries, enhancing the schema meaning.

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

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

Explicitly states 'Find tools by describing the data or task' and distinguishes from sibling tools (which are specific tools). Verb 'discover' and resource 'tools' are clear.

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 when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available and want to see the option set'. Clearly indicates when to use and implies alternatives.

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

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

Annotations already indicate read-only, non-destructive behavior. The description adds value by disclosing that results include pipeworx:// citation URIs and that the tool aggregates multiple sources. No contradiction with annotations.

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

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

The description is a single, well-structured paragraph. It front-loads the core purpose and then efficiently covers usage, return content, and parameter details without unnecessary words.

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

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

For a composite tool with no output schema, the description fully covers what the tool returns, how to use it, and when to use siblings. It leaves no ambiguity about the tool's capabilities or limitations.

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%. The description adds critical context: for `type`, it notes only 'company' is supported with future plans; for `value`, it explains ticker or zero-padded CIK and warns that names are not supported, directing users to resolve_entity. This significantly aids correct usage.

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: 'Get everything about a company in one call.' It lists specific data returned (SEC filings, fundamentals, patents, news, LEI) and distinguishes itself from sibling tools like resolve_entity by explaining when to use each.

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 trigger phrases are provided (e.g., 'tell me about X', 'research Microsoft'). It specifies when to use the tool vs alternatives (e.g., use resolve_entity if only a name is available) and positions it as a replacement for calling 10+ pack 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?

Annotations already declare destructiveHint=true. The description adds further behavioral context by mentioning clearing sensitive data, which enhances understanding of the tool's impact.

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, front-loads the action, and contains no redundant information, making it highly concise and well-structured.

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 deletion tool with one parameter and no output schema, the description covers purpose, usage, and behavioral context adequately, leaving no 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?

The schema provides 100% coverage for the single parameter 'key', with a clear description. The tool description adds no additional meaning beyond what the schema already offers, so baseline score applies.

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 deletes a memory by key, using a specific verb and resource. It also references sibling tools 'remember' and 'recall', aiding 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 lists use cases: when context is stale, task done, or clearing sensitive data. It suggests pairing with remember and recall, providing alternative tool context.

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

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

The description discloses important behavioral traits beyond the annotations: rate-limited to 5 per identifier per day, free, doesn't count against tool-call quota, and that the team reads digests daily. Annotations only state readOnlyHint=false, destructiveHint=false, so the description adds significant transparency about how the tool behaves.

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

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

The description is a single paragraph that is well-organized: starts with purpose, then usage conditions, then constraints. Every sentence adds value, though it could be slightly more concise by using bullet points. Still, it's clear and front-loaded.

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

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

Given the tool's three parameters (one nested), no output schema, and limited annotations, the description fully covers when, why, and how to use the tool. It includes limitations, impact (roadmap), and examples of appropriate content. No gaps remain.

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 100% coverage with descriptions for all parameters and nested fields. The description adds extra usage guidance (e.g., 'don't paste the end-user's prompt') that reinforces but does not fundamentally extend the schema meaning. Baseline 3, with a modest bump for helpful context.

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 for providing feedback to the Pipeworx team about bugs, features, data gaps, praise, or other. It specifies the action (tell) and resource (Pipeworx team), and distinguishes it from all sibling tools which are for data retrieval or analysis.

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 lists when to use the tool (bug, feature/data_gap, praise) and provides guidance on what to include ('in terms of Pipeworx tools/packs — don't paste the end-user's prompt') and what not to do. It also mentions rate limits and that it's free, giving clear context for selecting this tool over others.

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?

Annotations indicate readOnly and openWorld hints. The description adds rich behavioral context: walks child markets, groups them, checks monotonicity, returns ranked opportunities with reasoning. No contradiction.

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?

Concise yet informative; front-loaded with purpose, then mode explanations, then output description. 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?

For a 2-parameter, optional-parameter tool with no output schema, the description fully explains input modes, behavior, and output format. No missing 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 covers both parameters with descriptions. The tool description adds examples and explains how each parameter triggers a different mode, providing meaning beyond the schema.

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

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

The description clearly states the tool's purpose: finding arbitrage opportunities via monotonicity violations. It distinguishes two modes (event and topic) and explains when each applies, fully differentiating it from siblings.

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

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

Explicit guidance on when to use each mode, with a concrete example of cross-event mode catching cases missed by single-event mode. Provides clear 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?

Annotations already indicate readOnlyHint=true, openWorldHint=true, destructiveHint=false. The description adds specific behavioral details: groups by asset, fetches price history once, computes model probability, ranks by edge magnitude, and suggests trade direction. It also mentions data sources (FRED, Coinpaprika) and model type (lognormal). This provides useful context beyond annotations.

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

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

The description is a single paragraph of about 4 sentences. It is front-loaded with the primary purpose and uses precise language. Some technical details (lognormal model, FRED, coinpaprika) add depth but could be slightly more concise. Overall 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 no output schema, the description adequately explains what is returned (top N ranked by edge magnitude with suggested trade direction). For a read-only, 3-parameter tool with clear scope, the description provides sufficient context for an agent to understand the tool's capabilities and expected output.

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

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

Schema coverage is 100% with descriptions for all three parameters. The description adds context about the default values (10 for limit, 1wk for window, 0.5 for min_edge_pp) and the ranking logic. While not strictly necessary due to high schema coverage, the extra context helps understand how parameters affect results.

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 scans Polymarket markets, compares to Pipeworx model probabilities, and returns the top edges. It distinguishes itself from siblings like polmark_arbitrage by specifying it computes edge and suggests trade direction for crypto-price bets.

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 it's built for the 'what should I bet on today' question and helps discover opportunities without browsing hundreds of markets. However, it lacks explicit guidance on when not to use this tool versus alternatives, and does not mention prerequisites or exclusions like unsupported markets.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by specifying scoping to user identifier (anonymous IP, BYO key hash, or account ID) and the dual retrieval/list behavior, which annotations do not cover.

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

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

Three efficient sentences with no wasted words. Purpose, usage, and pairing are all front-loaded in the first line, with additional context in subsequent sentences.

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 1-param tool with no output schema, the description fully covers retrieval behavior, listing mode, scoping, and relationship to sibling tools. Nothing is missing.

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 one parameter 'key' has 100% schema coverage, but the description adds the critical nuance: omitting the key lists all saved keys. This goes beyond the schema's description.

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 a value saved via 'remember' or lists all keys when omitted. It uses specific verbs ('Retrieve', 'list') and distinguishes from siblings 'remember' and '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?

Explicitly says when to use: 'look up context the agent stored earlier' and implies alternatives: 'without re-deriving it from scratch'. Mentions pairing with 'remember' to save and 'forget' to delete.

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 reveals key behaviors: parallel fan-out to multiple sources, accepted date formats, and return structure (changes + count + URIs). This adds significant value beyond the annotations (readOnlyHint, openWorldHint), which only hint at safety and openness.

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 at three sentences. It front-loads the purpose, then provides usage examples, then details functionality. Every sentence earns its place with no redundancy.

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

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

Given the complexity and lack of output schema, the description adequately explains the tool's function and output type (structured changes, count, URIs). It falls short on full output structure details, but annotations fill some 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 100%, but the description enriches each parameter: explains date formats for 'since', ticker/CIK for 'value', and limits 'type' to 'company'. This provides nuance beyond the raw 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: retrieving recent changes for a company. It provides specific example queries and identifies three data sources (SEC EDGAR, GDELT, USPTO), making it distinguishable from sibling tools like entity_profile or bet_research.

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 includes explicit examples of when to use the tool ('what's happening with X?', 'any updates on Y?') and mentions monitoring. However, it does not specify when not to use it or suggest alternatives, leaving some ambiguity.

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

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

The description adds value beyond annotations by detailing persistence behavior and scoping by identifier. Annotations already indicate a write operation (readOnlyHint=false) and non-destructive nature, so the description complements them well.

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 (5 sentences) with a logical flow: purpose, usage timing, storage details, and pairing with other tools. No superfluous 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?

The description fully covers the tool's purpose, usage, persistence, and key-value structure. Given the simplicity of the tool (2 string params, no output schema), the description is comprehensive for an agent to decide and invoke correctly.

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

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

Schema coverage is 100% with good descriptions for both key and value. The description adds naming conventions ('subject_property', 'target_ticker') and clarifies value as 'any text', enhancing meaning beyond 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 data the agent will need to reuse later' with a specific verb and resource. It differentiates from siblings by naming recall and forget as companion tools.

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

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

The description explicitly tells when to use ('when you discover something worth carrying forward') and provides context on persistence (24h for anonymous, persistent for authenticated). It lacks only an explicit when-not-to-use statement.

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?

Annotations already mark as readOnly and non-destructive. Description adds behavioral details: returns IDs plus pipeworx:// citation URIs, which is beyond the schema and annotations.

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

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

Concise paragraph of 5 sentences, no redundancy. Purpose is front-loaded, 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?

Adequately covers purpose, IDs, examples, and usage order. Could mention error cases (not found), but not critical given the tool's nature.

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 100% with descriptions for both parameters. Description adds examples ('Apple' → AAPL) and context for value, improving understanding beyond 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?

Clear verb 'Look up the canonical/official identifier' with specific resources (company, drug) and ID systems (CIK, ticker, RxCUI, LEI). Distinguishes from sibling tools by stating it should be used before other tools that need identifiers.

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 usage context: 'Use when a user mentions a name and you need the CIK...' and 'Use this BEFORE calling other tools that need official identifiers.' Does not explicitly state when not to use, but sufficient 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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds no behavioral details beyond what annotations provide, such as response format or access limitations.

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 words) but at the cost of informativeness. It is under-specified rather than efficiently concise.

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

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

No output schema; description does not explain return values or additional context. Given the simple input but many sibling tools, the description is incomplete for reliable tool selection.

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 no description for the setlist_id parameter, and the tool description does not clarify its meaning or expected format (e.g., UUID, numeric ID). With 0% schema description coverage, the description fails to add value.

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

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

The description 'Single setlist.' is vague; it does not specify an action verb (e.g., retrieve, fetch) or resource clearly. It hints at retrieving one setlist but could also be interpreted as a static object. Compared to siblings like setlist_search, the purpose is unclear.

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 setlist_search, artist_setlists, or venue_setlists. The description offers no 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the description does not need to repeat this. However, it adds no additional behavioral context (e.g., how search results are structured or paginated). Given annotations, a score of 3 is adequate but not enhanced by the description.

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 brief (two words), but this is not conciseness—it is under-specification. There is no structure or front-loading of critical 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 13 parameters, no output schema, and absent parameter descriptions, the description is severely incomplete. The agent cannot determine how to construct a meaningful search query or interpret results.

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

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

With 0% schema description coverage over 13 parameters, the description must compensate by explaining parameter meaning. It does not provide any parameter details or examples, completely failing to support correct usage.

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 'Search setlists' is a tautology that restates the tool name without adding specificity. It fails to distinguish this tool from siblings like 'setlist', 'artist_setlists', or 'venue_setlists', which likely provide similar search functionality with different filters.

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. There are no explicit when-to-use, when-not-to-use, or alternative suggestions, leaving the agent without 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?

Annotations indicate readOnlyHint true and destructiveHint false, so the agent knows it's a safe read. However, the description adds no behavioral context beyond the schema, such as whether it returns full profile data or a summary.

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?

At two words, the description is severely under-specified, not concise. It lacks structure and does not earn its place; a sentence clarifying the tool's purpose would be valuable.

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

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

Given the simple input and no output schema, the description should at least hint at what the response contains (e.g., 'name, email, avatar'). The minimal description leaves the agent guessing about return value and 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?

With 0% schema coverage and a single required parameter, the description fails to explain the meaning or expected format of user_id. The agent has no hints about what constitutes a valid user identifier.

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 'User profile.' is a noun phrase, not a verb+resource. It vaguely implies retrieval but does not clearly state the action (get/retrieve). The name 'user' alone is ambiguous, and the description offers no improvement.

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

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

No guidance on when to use this tool versus alternatives like user_attended. No context about prerequisites or typical use cases.

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not contradict them. However, the description adds no extra behavioral context beyond what's in annotations, such as whether results are paginated, ordered, or what fields are returned. Given the annotations, a score of 3 is appropriate for not providing additional value.

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

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

The description is extremely concise at three words, which under-specifies the tool. While brevity is valued, this is too terse to be useful. It could be expanded to include parameter context or usage hints without being verbose.

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

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

Given the lack of an output schema and minimal parameter descriptions, the description is incomplete. An agent cannot determine what the tool returns or how to format inputs. For a simple query tool, more detail is needed for reliable usage.

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

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

Schema description coverage is 0%, and the description provides no details about parameters. The parameter 'p' is undocumented and its purpose is unclear. The description does not add meaning beyond the schema, which is already minimal. The agent cannot know how to use the parameters correctly.

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

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

The description 'User's attended shows.' clearly indicates the tool returns shows that a user attended. It specifies the resource (shows) and the verb (attended), and it implicitly differentiates from sibling tools like 'user' or 'setlist' by focusing on attendance. However, it could be more explicit about whether it lists shows or returns details.

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 alternatives. No mention of prerequisites, filtering, or when not to use it. The description provides no context for the agent to decide between this and sibling tools like 'user' or 'setlist_search'.

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?

Annotations indicate read-only and open-world hints, and the description adds value by detailing the return structure (verdict types, extracted form, actual value with citation, percent delta) and domain scope. No contradictions with annotations.

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

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

The description is very concise, two sentences plus a scope/return note, with no unnecessary words. It is front-loaded with the core action and efficiently provides key details.

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

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

Given no output schema, the description adequately explains return values and limits. It lacks detail on failure scenarios or coverage boundaries, but for a single-parameter tool, it is sufficiently 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 100% with a clear description of the 'claim' parameter. The description adds practical examples of claim formats, enhancing understanding beyond the schema.

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

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

The description clearly states the tool's purpose: fact-check factual claims against authoritative sources, specifying it handles company-financial claims for US public companies via SEC EDGAR. This distinguishes it from sibling tools like compare_entities or bet_research.

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

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

The description provides explicit guidance on when to use the tool ('when an agent needs to check whether something a user said is true') and includes example phrasings. However, it does not explicitly state when not to use it or suggest alternatives, though siblings are listed.

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 does not disclose any behavioral traits beyond what annotations already provide. The openWorldHint annotation suggests unpredictable results, but the description offers no elaboration. This is a missed opportunity.

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?

While extremely short, the description sacrifices clarity for brevity. It does not earn its place as it provides no useful information beyond the tool name.

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

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

The description is minimal and fails to provide any contextual completeness. With open world hint and no output schema, the agent has no guidance on what the tool returns or how the parameter should be used.

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 a single 'id' parameter with no description. The tool description does not clarify what the id represents (e.g., venue ID, event ID). With 0% schema description coverage, the description should provide semantic meaning for the parameter, but it fails to do so.

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 'Venue detail.' is a tautology (restates the name 'venue') and provides no verb or action. It does not differentiate from sibling tools like venue_search or venue_setlists.

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

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

No usage guidelines provided. The description does not indicate when to use this tool over others, such as when the venue id is known vs needing to search.

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?

Annotations already indicate readOnlyHint=true and openWorldHint=true, but the description adds no additional behavioral context such as result limits, pagination, or that it covers multiple venue fields.

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 short (two words), but it is under-specified rather than effectively concise. It omits necessary details and does not earn 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 7 parameters, no output schema, and multiple sibling tools, the description is grossly incomplete. It does not explain return values, filtering behavior, or how to effectively use the 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% with 7 parameters, and the description provides no explanation of parameters. It completely fails to add meaning beyond the raw 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 states 'Search venues.' which is a clear verb-resource pair, but it lacks specificity on what fields can be searched and does not distinguish from sibling tools like 'venue' (singular) or 'venue_setlists'.

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. With siblings like 'venue' and 'venue_setlists', the description should indicate typical search 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?

Annotations already indicate the tool is read-only and non-destructive. The description adds no behavioral context beyond stating the resource 'setlists at a venue.' It does not explain what data is returned, pagination, or how the optional 'p' parameter affects results.

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

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

While very short (four words), the description sacrifices essential information for brevity. Conciseness should not come at the cost of completeness; a single phrase without verb or context is insufficient for an agent to understand the 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?

Given the presence of two parameters and multiple sibling tools, the description is woefully incomplete. It does not specify the return value (even though no output schema exists), how to use the parameters, or any constraints. The agent has no basis to correctly invoke this tool.

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

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

With 0% schema description coverage, the description provides no explanation for the two parameters ('id' string, 'p' number). The name 'id' is ambiguous (venue ID? setlist ID?), and 'p' is completely unexplained. The description fails to compensate for the missing schema 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 'Setlists at a venue.' simply restates the tool name 'venue_setlists' in a phrase, lacking an explicit verb or action. It does not clarify whether the tool retrieves, lists, or searches setlists, making it tautological.

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

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

No guidance on when to use this tool versus alternatives like venue (venue info), setlist_search (search all setlists), or artist_setlists (by artist). The context is only implied from the name, with no explicit instructions or exclusions.

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