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

No annotations are provided, so the description carries full behavioral burden. It says nothing about required permissions, whether the issue is mutable afterward, or what the caller receives. Only the implicit creation semantics are conveyed.

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?

A single short sentence with zero waste, front-loading the verb and resource immediately.

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 mutation tool with no annotations and no output schema, the description omits permissions, response behavior, and sibling routing. The schema documents parameters, but key behavioral context 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?

Schema description coverage is 100%, so all 5 parameters are documented in the schema itself. The description adds no field-level semantics beyond the verb/resource, so baseline 3 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?

States a specific verb and resource ('新建 Issue'), clear enough to distinguish from read-only siblings like list_issues or get_repo_stats. Not a 5 because it does not explicitly name or differentiate from the closest sibling update_issue.

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 parenthetical '收需求/建任务' implies intended use cases (collect requests / create tasks), giving implied guidance. But it does not state when to prefer this over update_issue or when-not to use.

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

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

With no annotations, the description carries the full burden. It does add real context: output is in Chinese and the changelog is composed from commits because Gitee has no native API, which signals derivation and potential fidelity limits. However, it says nothing about permissions, rate limits, where the changelog is written/returned, or whether repeat calls are idempotent.

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?

A single compact sentence with the core action front-loaded and the caveat appended in parentheses. No wasted text.

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

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

There is no output schema and no annotations, yet the description does not say what is returned (markdown string? file path?), nor how the commit range interacts with since_tag/max. It is adequate for invocation but leaves the agent guessing about 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?

Schema description coverage is 100%, so all four parameters (owner, repo, max, since_tag) are already documented in the schema. The description adds no parameter-level semantics beyond that, so the baseline of 3 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 states a specific verb+resource: generate a Chinese CHANGELOG from recent commits. It is clearly distinguishable from the sibling list (stats, stargazers, issues, etc.), though it does not explicitly name which sibling to prefer. The parenthetical clarifies the generation mechanism.

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 explicit when-to-use guidance, no prerequisites (e.g., whether the repo must have tags, whether commits must exist), and no mention of alternatives. The only usage signal is implicit in '基于最近 commit'. An agent gets no routing help beyond 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?

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only aggregation but says nothing about authentication requirements, rate limits, caching/staleness of the counts, or whether private repos are supported — all relevant for a stats endpoint.

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?

A single compact sentence that front-loads the action and then lists the returned metrics. No filler, though it trades brevity for leaving behavior and usage unspecified.

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 two-parameter read tool with full schema coverage, the description is largely sufficient, and it usefully enumerates the returned metrics given no output schema exists. It lacks any note on auth or freshness, which is a minor gap.

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 both parameters (owner, repo) are documented with examples in the schema, so the baseline is 3. The description adds no syntax or format detail beyond what the schema already 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 (获取 Gitee 仓库统计) and enumerates what is aggregated: star/fork/watch counts and open issue count. This distinguishes it from siblings like list_stargazers and list_issues, which enumerate individual items rather than return counts, though the differentiation is implicit rather than stated.

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 statement of when to use this tool versus list_stargazers or list_issues, and no prerequisites (e.g., whether the repo must be public or whether auth is required). Usage is only implied by the fact that it returns counts.

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 does not disclose that this is a read-only operation, how many issues are returned, pagination behavior, or ordering. For a listing tool with zero structured behavioral hints, this is a significant gap.

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?

A single front-loaded sentence with no filler; the resource and its filter capability come first. It is appropriately sized for an operation of this simplicity, though slightly terse given the missing behavioral 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?

The core purpose and filters are covered, but with no annotations and no output schema the description should say more about the read-only nature and return/pagination behavior. Adequate but with clear gaps for a 4-parameter listing 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 100%, so repo, owner, state, and labels are already documented in the schema, including the state enum default. The description's mention of state/label filtering adds no syntax or format detail beyond what the schema provides, so the baseline 3 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?

States a specific verb+resource ('列出仓库 Issue') plus the supported filtering axes, so an agent knows this is a read-list tool. It does not differentiate itself from siblings like get_repo_stats or list_stargazers, but the verb/resource pair is unambiguous against create_issue/update_issue.

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 sentence describes capability ('支持按状态/标签过滤') rather than when to pick this tool over get_repo_stats, list_stargazers, or the create/update siblings. No prerequisites, no exclusions, no alternative routing – usage is only implied by 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?

Without annotations, the description carries full burden and does disclose key behavioral traits: it requires a PAT, and without credentials it falls back to mock data. This is valuable context about authentication and data reliability. However, it doesn't cover pagination behavior, rate limits, or return format details.

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?

A single, concise sentence that packs the core purpose and critical credential behavior without any waste. Front-loads the main action and appends the important auth caveat.

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 (list operation, 3 params, no output schema, no annotations), the description covers the essential purpose and the auth/mock behavior. It could be more complete by mentioning pagination or return format, but is largely sufficient 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?

Schema description coverage is 100%, so the schema already documents all three parameters (page, repo, owner) with descriptions. The description adds no parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

States a specific verb (list) and resource (stargazers/users who starred the repo), clearly distinguishing this from siblings like get_repo_stats or list_issues. An agent can immediately understand the tool lists users who starred a repository.

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?

Implies usage context by noting PAT requirement and mock fallback, but does not explicitly state when to use this tool versus alternatives. No guidance on prerequisites or when-not-to-use scenarios beyond the credential note.

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 for a mutation tool. It never states whether omitted fields (state or labels) are left unchanged, whether the update is partial or full-replace, what permissions are required, or whether closing is reversible. The '(自动打标签/关单)' phrasing is vague about what actually happens on the server side.

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?

A single short sentence with the resource front-loaded and no filler. It is efficient, though the parenthetical is cryptic rather than informative, so it is not maximally 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 five-parameter mutation tool with no annotations, no output schema, and no return-value documentation, the description is far too thin. It leaves the agent without knowledge of partial-update semantics, permission requirements, or the effect of the automatic labeling/closing behavior it alludes to.

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 all five parameters (owner, repo, number, state, labels) are documented in the schema, so the baseline is 3. The description echoes state and labels but adds no format or constraint detail beyond the schema's enum and comma-separated hint.

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+resource ('更新 Issue 状态或标签') and names the two mutable fields, which distinguishes it from list_issues, create_issue, and the read-only siblings. It stops short of explicit sibling differentiation, but the verb+resource pairing is unambiguous.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as create_issue when a new issue is needed. The parenthetical '(自动打标签/关单)' hints at automatic labeling/closing but does not explain the conditions under which an agent should invoke the tool.

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