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

With no annotations, the description carries the behavioral burden. It discloses the return format as a table, lists the exact data points, and signals imprecision with 'approximate contributor count'. It does not mention rate limits or network dependency, but the compare operation is clearly non-mutating and well described.

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

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

Two sentences with no filler. The first sentence front-loads the action, input count, and output contents; the second gives usage positioning. Every sentence earns its place.

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

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

The description tells the agent exactly what to input and what fields will appear in the result, which is enough for a simple comparison tool with one well-schema'd parameter. Minor caveats about error behavior or rate limits are not stated, but they are not essential for correct invocation.

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

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

The schema already fully documents the single 'repos' parameter with min/max items and an example. The description repeats the 2-4 constraint and GitHub scope but adds no meaningful semantics beyond the schema. Baseline 3 is appropriate given the 100% schema coverage.

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

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

The description uses the specific verb 'Compare', names the resource '2-4 GitHub repos', and states the output form: 'side by side as a table' with a clear list of fields. This distinguishes it from sibling tools like search_github_repos and get_repo_overview.

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 'Use this to help decide between finalists after search_github_repos', giving a clear when-to-use context. It contrasts with 'eyeballing separate results' but does not name alternative tools for when not to use it, so it stops short of a full exclusion set.

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 transparency burden. It explicitly states that text file contents are returned and that binary files are refused with a link, which covers the main behavioral aspects. It does not mention auth requirements or side effects, but for a read-only operation, this is sufficient.

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 that efficiently cover purpose, usage guidance, and limitations. There is no redundant or extraneous information, and the structure is clear and direct.

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 two well-described parameters and no output schema, the description provides all necessary context: what it does, when to use it (including a hint about the sibling tool), and how it handles binary files. Nothing essential 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?

Both parameters (repo and path) are fully described in the schema with examples, achieving 100% schema description coverage. The description itself adds no additional parameter-specific context, so it does not enhance beyond the schema. This aligns with the baseline of 3 for high schema coverage.

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

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

The description clearly states the tool's purpose: to read the contents of a single text file. It distinguishes itself from get_repo_structure by noting that it retrieves file contents rather than structure, and it specifies that binary files are refused, setting clear boundaries.

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 this tool: it advises using get_repo_structure first if the exact path is unknown, and it warns that binary files are not supported, redirecting users with a link. This gives clear when-to and when-not-to usage instructions.

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 explaining behavior. It does so effectively by disclosing the optional branch scoping and what each returned entry contains. It could mention ordering or lack of diffs, but the behavior is clear and unlikely to surprise the agent.

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 with no filler. The first sentence states the action, scope, and purpose; the second describes the return value. Every word earns its place, and the most important information is front-loaded.

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

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

The description is complete enough for a straightforward read-only listing tool. It explains the return shape despite the absence of an output schema, and parameter details are fully covered by the schema. A minor gap is that it doesn't explicitly mention sorting order, but 'most recent' implies chronological order, so this is not a significant omission.

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 already provides complete descriptions for all three parameters, including format, defaults, bounds, and the meaning of omitting `branch`. The description adds no meaningful parameter-level detail beyond reinforcing that branch is optional, so the baseline score of 3 is appropriate.

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 ('Get the most recent commits') with a well-defined resource and scope ('to a repo (or one branch)'). It also distinguishes itself from sibling tools by focusing on commit history rather than repos, branches, or file contents. The addition of the output fields ('short SHA, author, when it happened, and the commit message') further clarifies what the tool is for.

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 phrase 'to see what's actively being worked on' provides clear contextual guidance on when to use this tool. It does not explicitly name alternatives or exclusions, but for a simple read-only commit listing tool, this level of usage context is sufficient.

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 transparently lists what the tool returns and even adds precision with 'approximate contributor count' and 'README preview,' which prevents over-expectations. It does not mention rate limits, error behavior, or data freshness, but for a read-only snapshot tool the disclosed output surface is fairly complete.

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

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

Two sentences with no filler. The first sentence front-loads the operation and output fields; the second gives a clear usage directive. Every part contributes to selection and invocation.

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 single-parameter tool with no output schema and no annotations, the description is nearly complete: it covers the input source, the full set of return values, and the intended workflow position. The only minor gaps are exact response formatting, error handling, and potential rate/resource limits, which are not critical for an overview snapshot.

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

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

Schema description coverage is 100%: the input schema already explains the 'owner/name' format, accepts GitHub URLs, and notes that the value is usually copied from a search result. The main description adds only that the repo is 'one specific GitHub repo,' which does not materially go beyond the schema. A baseline 3 is appropriate when the schema already handles parameter 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?

The description opens with a specific verb and resource: 'Get a snapshot of one specific GitHub repo,' then enumerates the exact data categories returned (description, stars/forks/open issues, license, topics, languages, latest release, contributor count, README preview). This clearly differentiates it from search-oriented siblings like search_github_repos and code-focused tools like get_file_content.

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

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

The description provides explicit workflow context: 'Use this after search_github_repos to understand a specific candidate before diving into its code.' This tells the agent when in the discovery flow the tool belongs and signals that it is a pre-code step. It does not name explicit alternatives or exclusion conditions for siblings like compare_repos or get_repo_structure, so it stops short of a 5.

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 behavioral burden. It explicitly discloses that listing is one level at a time, that omitting path returns the root, and that repeated calls navigate deeper. It does not mention output formatting, ordering, or edge cases, but the core behavior is transparent.

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

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

Two concise sentences front-load the core action and then give the key usage pattern. Every sentence earns its place; there is no redundant or filler content.

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 relatively simple browsing tool with complete schema description and no output schema, the description is nearly sufficient. It explains how to start and how to go deeper, though it could be slightly more explicit about what the returned listing contains beyond 'files and folders'.

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%, so the baseline is 3. The description adds value beyond the schema by explaining path semantics ('Start with no path to see the root') and providing an example ('src'), which helps the agent correctly omit or supply the path 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 uses a specific verb ('List') and a clear resource ('files and folders at a path inside a repo'), and distinguishes this tool from sibling tools by describing directory-structure browsing rather than file content or branch listing. The file-tree analogy makes the purpose immediately understandable.

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 practical guidance: start at the root by omitting path, then call again with a subdirectory path to go deeper. It does not explicitly compare against alternatives like get_file_content or list_branches, but the step-by-step usage context is strong and unambiguous.

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 behavioral burden. It transparently discloses that this is an approximation because GitHub has no official trending endpoint, explains the created-within-window logic, and states ranking by stars accumulated. It does not cover output shape or pagination, but the core approximation behavior is well communicated.

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

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

Two information-dense sentences with no filler. The core behavior is front-loaded, and the approximation rationale plus sibling distinction fit naturally in the second sentence.

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 no-output-schema, no-annotation tool, the description covers purpose, approximation method, ranking logic, use case, and the key alternative. The input schema fully documents parameters, making this sufficient for an agent to select and call 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 100%, and the schema already documents the since enum and all filter properties with defaults and limits. The description reinforces the time-window concept and ranking, but adds minimal new meaning beyond structured field descriptions.

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

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

The description opens with a specific verb and resource ('Surface repos that are new and already gaining traction'), clearly defining what the tool does. It also differentiates itself from search_github_repos, so an agent can distinguish it without opening the schema.

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 says the tool is good for open-ended exploration like 'what's hot in agent frameworks right now' and contrasts it with search_github_repos, which 'needs a specific query.' This is a clear when-to-use/alternative guidance.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains that the tool lists branches and the commit each points to, and implies a read-only operation, but it does not mention potential limits, pagination, or lack of side effects beyond what the schema already states.

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. The primary capability is front-loaded in the first sentence, and the second sentence provides practical context without 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 straightforward list operation, the description covers what the tool does and when it is useful. There is no output schema, but the stated output — branches and their commits — is clear enough for an agent to know what to expect.

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%, so the schema already documents both parameters, 'repo' and 'limit'. The description does not add extra semantic detail about parameters, but it does not need to; the schema is sufficient.

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 a specific verb and resource: 'List branches in a repo' and adds the useful detail that it returns the commit each branch points to. This clearly distinguishes it from sibling tools like get_repo_overview or get_recent_commits.

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 concrete use cases: finding active feature branches and confirming the default branch name before calling other tools. It does not explicitly state when not to use it or name alternative tools, but the provided context is enough to guide appropriate 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 behavioral burden. It does disclose a key behavior—matching curated GitHub topic tags rather than description text—and provides examples. However, it does not mention result ordering, pagination, error behavior, or any constraints on topic matching beyond lowercase/hyphenated guidance in the schema.

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

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

Two sentences with no filler. The core action and examples come first, and the usage guidance is concise and immediately actionable.

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 rich schema covering all parameters and the clear differentiator from sibling tools, the description is nearly complete. The only notable gap is the lack of any statement about the return shape, and without an output schema the agent must infer that the result is a list of repository records.

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%, so the schema already documents the topic and filter parameters well. The description adds useful context about what a topic tag is and how it differs from free-text, but it does not need to explain parameter syntax since the schema covers it.

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 a specific verb ('Find') and resource ('GitHub repositories') and narrows the operation to topic-label matching. It explicitly contrasts with free-text search, distinguishing this tool from sibling search_github_repos without needing to inspect the schema.

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 gives clear guidance: use this tool when you already know the ecosystem's term for the topic, and frames it as more precise than free-text search. This effectively routes the agent between search_by_topic and search_github_repos with an explicit condition.

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 behavioral disclosure burden, and it delivers: it reveals the ranking blend (stars and maintenance recency) and the return shape (a short usefulness summary per repo). It does not disclose rate limits or result-count behavior, but for a read-only search tool the disclosed traits are the key ones.

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 sentences with no waste: action/scope, ranking+output behavior, and usage examples. Each sentence earns its place and the core behavior is front-loaded in the first sentence.

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 moderate complexity (2 params, one nested object, no output schema, no annotations), the description covers the essential gaps: return value shape and ranking rationale. It is not exhaustive — result count, pagination, and explicit sibling differentiation are absent — but nothing an agent needs to call it correctly is critically 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?

Schema description coverage is 100%, so the baseline is 3; the schema already documents query phrasing and each filter parameter. The description's example queries add minor illustrative value but no new parameter information beyond what the schema provides.

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 a specific verb and resource — 'Search GitHub for open-source repositories' — and gives the context (research topic, technology, project idea) plus example request phrasings. It stops short of 5 because it never names a sibling (e.g., search_by_topic) or explicitly says how it differs from them, though the ranking-and-summary output description partially distinguishes it.

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?

'Good for requests like...' with two concrete examples ('find me RAG implementation repos', 'show me containerization examples in Go') establishes clear when-to-use context. It lacks explicit when-not-to-use guidance or routing to alternatives among the eight sibling tools, so it does not earn a 5.

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