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

With no annotations, the description carries the full burden. It discloses that it does not code, forces coverage of jury weights, and returns a specific structure (day-by-day tasks mapped to categories). This is transparent behavior, though it omits details like error handling or side effects. For a plan generator, this is adequate.

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

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

The description is three sentences, front-loading the main function, then adding constraints and an example. Every sentence earns its place with no fluff. The structure is logical 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 the output structure well (day-by-day tasks mapped to Technical/Innovation/Impact/Design/Completion plus video script slot). It also clarifies it does not code. It does not mention prerequisites like track validity, but this is minor given the simplicity and sibling context. Overall complete enough for an agent to call 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 0%, so the description must explain both parameters. It does so clearly: 'input track+idea' and the example uses 'track1' and a specific idea string. Both parameters are fully explained with a concrete example, adding meaning beyond the bare schema.

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

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

The description clearly states the tool's function: input track+idea returns a 48h task breakdown and checklist. It specifies the resource and action, and differentiates from siblings by noting it does NOT code and focuses on jury weights. The example further clarifies the output.

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

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

The description implies when to use this tool (to generate a plan from track and idea) and gives an example. It does not explicitly name alternatives or conditions for not using it, but the 'does NOT code' note and focus on jury weights provide context. Clear but not fully explicit.

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 disclose behavior. It only says the tool is a 'digest' of rules, implying a summary, but does not explain whether it is read-only, what format the rules come in, or if there are any side effects. The burden is on the description, and it falls short.

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, front-loaded sentence that immediately states the purpose and usage. Every word adds value, and there is no fluff or redundancy. It is efficiently 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 zero-parameter, simple rules-digest tool, the description covers the essential information: what it provides and when to call. It does not describe the output format, but that is likely self-explanatory given the name. The description is sufficient for an agent to decide to invoke it, though more detail on the digest's content would raise it to a 5.

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

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

The tool has zero parameters, so the schema is empty. Per guidelines, a 0-parameter tool gets a baseline of 4. The description doesn't need to add parameter details since there are none, and it correctly avoids mentioning nonexistent inputs.

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

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

The description clearly states the tool provides 'Bases/rules of the whole hackathon' and explicitly says 'Call when AI needs event rules.' It names the resource (rules) and the trigger condition. No sibling appears to cover the same function, so it stands distinct.

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?

It provides an explicit usage condition ('Call when AI needs event rules'), which tells the agent when to invoke it. It does not mention alternatives or exclusions, but given the specific condition and lack of similar siblings, this is adequate.

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

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

With no annotations, the description carries the full burden. It discloses that the tool returns a rubric that the agent must self-fill, and that it includes a compliance verdict. It does not mention whether the tool is read-only, stores data, or has side effects, but for a feedback tool this is likely non-destructive. The description adds value by explaining the interactive nature (self-fill) and the verdict, but it lacks detail on potential edge cases or error conditions.

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

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

The description is a single concise sentence followed by a short instruction. It front-loads the workflow with 'How it works' and then a clear arrow representation. Every word contributes: input, output, scoring details, and timing. No redundancy or filler.

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

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

For a simple tool with one parameter and no output schema, the description covers the essential aspects: what to input, what to expect (rubric + verdict), and when to use it. It does not list the specific criteria in the rubric, but that is presumably returned by the tool itself. The description is sufficient for an agent to understand how to invoke it and interpret the result.

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 only the parameter name 'design_notes' with no description (0% coverage). The description compensates by explaining the input as 'paste design/code summary,' clarifying what design_notes should contain. This adds meaningful context beyond the schema. However, it does not specify format, length, or examples, so it is not exhaustive but adequate for a single string parameter.

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

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

The description clearly states the tool's function: it returns a scoring rubric and compliance verdict based on pasted design/code summary. The verb 'returns' and resource 'scoring rubric' are specific. It also mentions the self-fill nature and the 0-10 scoring, which distinguishes it from generic feedback tools. It does not explicitly name siblings, but the unique combination of rubric + verdict is clear enough to avoid confusion.

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

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

The description explicitly says 'Run BEFORE coding and BEFORE delivery,' providing clear timing guidance. It also implies the input is a design/code summary. It does not explicitly mention alternatives or when not to use it, but the timing is a strong usage signal. The flow 'How it works' also indicates the intended workflow.

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. It states the tool scans notes for patterns, but it does not describe whether it is read-only, what side effects occur (if any), whether it returns a result, or what happens when patterns are found. This leaves significant ambiguity for a tool that could have safety implications.

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 that is direct and front-loaded with the key action and purpose. It contains no filler or redundant information, making it highly concise and easy to parse.

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 what the tool returns (e.g., pass/fail, list of violations). It does not. It also lacks any detail on constraints or expected input quality, making it incomplete for an agent to understand the full context of calling 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?

Schema description coverage is 0%, so the description must compensate. The description clarifies that 'design_notes' refers to design/code notes, adding some meaning beyond the parameter name. However, it does not specify the expected format, length limits, or how the notes are interpreted, leaving gaps that the schema cannot fill.

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

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

The description clearly states the action ('scans') and the resource ('design/code notes') and the specific purpose ('for cloud-inference patterns'). It distinguishes itself from siblings like qvac_search and qvac_index, which are about retrieval, making this a distinct guardrail 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 does not provide any guidance on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or explicit exclusions. The agent must infer usage from the single sentence, which is not sufficient for proper tool selection.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions 'allowlisted' (restrictions) and 'plain text' (output format), but does not cover error conditions, authentication, rate limits, or the behavior of the max_chars parameter. This is insufficient for a tool with no structured behavioral metadata.

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 concise sentences with no filler. The primary action is front-loaded, and the reference to qvac_index is efficient and relevant.

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

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

The description covers the core purpose and gives a critical usage hint (use qvac_index URLs). However, it omits details about max_chars, error handling for non-allowlisted URLs, and the exact response structure, making it only minimally adequate for a two-parameter tool with no annotations or 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 description coverage is 0%, so the description must compensate. It does not explain either parameter beyond implying url comes from qvac_index, and it completely ignores max_chars. No parameter semantics are provided.

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 a specific action (Fetch), a specific resource (one allowlisted QVAC page), and the output format (plain text). It also references qvac_index as the source for URLs, which helps differentiate it from listing/searching 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 provides clear context by directing the agent to use URLs from qvac_index, implying a prerequisite step. However, it does not explicitly state when not to use this tool or compare it to alternatives like qvac_search, so it falls short of full usage 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?

No annotations are provided, so the description must carry the full behavioral burden. It only states it's a curated map and to call it first. It does not disclose whether it's read-only, what the return format is, or any side effects. This is a significant gap for a tool that presumably returns data to guide subsequent actions.

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 short sentences with zero waste. It front-loads the core purpose ('Curated map') and immediately gives the usage directive. Every word contributes 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?

For a tool with no parameters and no output schema, the description is adequate. It explains the tool's role and its relation to qvac_fetch. It could optionally mention that the result is a list of URLs or something similar, but given the simplicity and the clear chaining instruction, 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?

The tool has zero parameters and the schema is empty, so per guidelines the baseline is 4. The description adds no parameter-specific information because there are none to describe.

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

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

The description clearly states the tool provides a curated map of QVAC's functions and where to read about them. It distinguishes itself by instructing to call it before qvac_fetch, implying it's a starting point. However, it doesn't explicitly name the alternative tools it complements, though the sibling list implies this.

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

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

The description gives explicit usage guidance: 'Call first, then qvac_fetch(url).' This tells the agent exactly when to invoke it relative to qvac_fetch. It doesn't mention when not to use it or alternative scenarios, but the directive is clear for the primary workflow.

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

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

No annotations are provided, so the description carries the full burden. It only states the filtering action and gives examples, but does not disclose return format, whether results are paginated, case sensitivity, or side effects. For a search tool, this is minimal disclosure.

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, focused sentence that leads with the core action and resource, followed by illustrative examples. Every word earns its place, with no redundancy or unnecessary detail.

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 search tool, the description covers the basic purpose and parameter meaning, but it omits return-value expectations or any note about read-only nature. Given the absence of an output schema and annotations, this is a moderate gap for an agent deciding how to use the result.

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 string parameter 'keyword' with 0% coverage. The description adds value by explaining that the keyword is used to filter the QVAC index and providing example values, which helps the agent understand the expected input. However, it does not specify format constraints or possible invalid values.

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 a specific verb ('filter') and a resource ('QVAC index'), with concrete keyword examples. It distinguishes the tool's purpose as a search/filter operation, though it does not explicitly differentiate it from siblings like qvac_index or qvac_fetch.

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 implies a keyword-search context but does not mention exclusions or direct users to other tools for listing or fetching. With several sibling tools, this lack of routing guidance is a notable gap.

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 disclosing behavior. It only says 'ONE-PARAGRAPH summary only,' which implies a read-only action but omits any detail on output format, side effects, permissions, or limitations. This is insufficient for a tool with zero annotation support.

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—a single sentence—but brevity here is under-specification rather than conciseness. It lacks any structured breakdown of purpose or behavior, and the one piece of information it does give ('ONE-PARAGRAPH summary only') is not meaningful without context.

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 one parameter, no output schema, and no annotations, the description should still explain what the tool does and what 'which' means. It does neither, making it impossible for an agent to know what to expect or how to use it correctly, even though the tool itself is simple.

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% and the description does not explain the 'which' parameter beyond referencing it in the track_detail call. It fails to clarify what values are valid, what the default 'track1' means, or how it affects the result, leaving the agent without essential semantic guidance.

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 it provides a one-paragraph summary but never defines what a 'track' is or what the summary covers. It references track_detail as the full spec, implying a relationship, but the core resource and action remain vague, offering no differentiation from siblings like qvac_index or hackathon_rules.

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?

It explicitly names track_detail as the alternative for a full spec, which is a useful pointer. However, it does not state when to choose this tool over track_detail or other siblings beyond a vague 'summary only' hint, so the decision criteria are incomplete.

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

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

With no annotations, the description must carry the full burden of behavioral disclosure. It states the output is a verbatim full file and gives a size estimate for track 1, but it does not disclose read-only behavior, potential size limits for other tracks, or any error conditions. It is minimal and lacks explicit safety or side-effect information.

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-loads the core concept, but the second sentence ('Track 1 = ~9k chars transcribed docx.') is a specific detail that may confuse rather than clarify. It is not well-structured for an agent to parse quickly.

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

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

Given the single optional parameter, no output schema, and no annotations, the description is severely incomplete. It fails to explain what the tool actually returns in a general sense, what inputs are valid, or what the output format is. An agent would struggle to call this tool correctly without additional context.

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

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

The schema has zero coverage for the 'which' parameter, and the description provides almost no semantic detail. It only mentions 'Track 1' but does not explain valid values, format, or how to request other tracks. The agent cannot infer the correct parameter usage from the 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 indicates the tool returns an entire track brief verbatim, but it is vague about what a 'track' is and how the selection works. It mentions Track 1 as an example but does not clearly state the verb+resource pattern (e.g., 'Returns the full brief for a specified track'). It is not a tautology, but it lacks explicit distinction from siblings like track_brief.

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 such as track_brief or qvac_fetch. The description does not mention exclusions, context, or comparative advantages, leaving the agent to guess based on the name.

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