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

With no annotations provided, the description carries the full behavioral burden and meets it well. It discloses the empty-ids special case, the allowed status values, the irreversible transition from completed, and the semantic warning that received does not mean task completion.

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 compact and front-loaded with the main purpose. Every clause earns its place: purpose, empty-ids rule, status enumeration, state constraint, and update requirement. There is no redundant 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?

Despite a rich behavioral summary, the description is incomplete for a 5-parameter tool with zero schema coverage and no annotations. It does not explain the required agent field, what result should contain, or how project is used. The output schema mitigates return-value ambiguity but not the input ambiguity.

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 by explaining parameter meanings. It covers status and partly ids, but the required agent parameter and the result/project parameters receive no explanation. An agent cannot confidently fill all fields from the description alone.

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 opening phrase '记录回执状态' clearly identifies a specific verb and resource: recording acknowledgment/receipt statuses. The description further distinguishes this from siblings like send_note and read_notes by focusing on ack state transitions rather than sending or reading messages.

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 usage conditions: empty ids means acknowledging only undelivered/unacked messages for the current agent, while updating existing acknowledgments requires explicit ids. It does not explicitly name alternatives, but the conditions are clear enough to guide when to call this tool.

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 available, the description carries the behavioral burden. It discloses the return behavior (conflict list or explicit '没有冲突') and an important edge case: expired claims are not conflicts but trigger a hint about the original terminal. An explicit statement that the tool is read-only would make it fully 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?

Four compact sentences cover purpose, timing, input format, output behavior, and an edge case, with no filler. The key action 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 covers when to use the tool, how to format files, what output to expect, and how expired claims are handled; an output schema also exists. The only residual gap is the unstated semantics of the optional agent/project parameters.

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 provides the required format for the 'files' parameter ('用逗号分隔'), which is valuable, but it leaves the optional 'agent' and 'project' parameters unexplained.

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 '查冲突' and immediately clarifies the resource ('files') and the purpose ('确认这些文件没有被别人占用'). It clearly distinguishes the tool as a check operation relative to the sibling claim/release 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?

It explicitly states when to call the tool: '开工前或收尾前调用'. It does not name alternatives or give exclusion conditions, but the timing guidance provides a clear selection 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?

With no annotations provided, the description carries the full burden. It discloses important behavioral traits: overlapping claims are rejected with the conflicting party named, repeated claims renew the TTL, and non-overlapping claims are retained. It does not mention TTL duration or explicit release requirements, but the core state-changing behavior is well covered.

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 front-loaded with the purpose, then explains conflict/renewal behavior, and ends with a compact parameter list. Every sentence adds useful information without 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?

Given there are no annotations and there is meaningful behavioral complexity, the description is largely complete: it covers claiming semantics, conflict rejection, renewal, TTL reset, and file format. Minor gaps include the undocumented optional project parameter and the lack of explicit guidance to use release_claim when done, but these are not critical for invoking 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. It provides meaningful descriptions for agent, task, and files, including a comma-separated format example. The optional project parameter is not explained, which prevents a perfect score.

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

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

The description clearly defines claim_files as a declaration of identity, task, and target files: '声明我是谁、我在做什么、我要动哪些文件'. This distinguishes it from sibling tools like release_claim and check_conflict by specifying the claim operation and its resource (files).

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 clear context for when this tool is used: to claim files before working on them, with conflict rejection if other terminals already hold overlapping claims. It also explains renewal behavior for repeated claims by the same agent. It does not explicitly name alternatives or say when not to use it, but the usage context is evident.

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 filling the agent parameter will prepend unread directed messages and mark them as delivered (a side effect), and explains the behavior when not filled. It also states it returns the Markdown file content. This is transparent about the conditional behavior, which is critical for a tool with an optional side-effect parameter.

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 concise paragraph that front-loads the purpose and then explains the optional parameter. Each sentence adds value, and it avoids fluff. It's appropriately sized for a tool with two optional parameters.

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 for the main function, and the presence of an output schema likely covers the return format. However, the project parameter is left unexplained, which is a gap given the schema has no description. It also doesn't mention error conditions, but for a read operation with optional parameters, this may be acceptable. The missing project parameter explanation prevents a higher score.

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 description thoroughly explains the agent parameter, including its purpose and side effects. However, it does not mention the project parameter at all, despite schema coverage being 0%. Since there are two parameters and only one is explained, the description only partially compensates for the schema's lack of 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 clearly states the tool reads the project's shared announcements (kanban) and returns the Markdown file content, listing the specific sections (claim area, shared decisions, latest changes). This is a specific verb-resource pair that distinguishes it from siblings like send_note or read_notes, making its purpose 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?

It explicitly says '开工前必看' (must read before starting work), providing a clear context for when to use it. It also explains that tasks sent via send_note are received here, which guides the agent to use this tool to check for assigned work. However, it does not explicitly state when not to use it or compare with alternatives like read_notes, though the context implies it.

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 and does well: it discloses idempotency, no-overwrite behavior, automatic detection order for project, and the side effect of creating a .board-project marker in non-git directories plus persistent project binding.

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 organized into clear sections and front-loads the initialization purpose. The only slight excess is the metaphor about installing a pre-work board for the AI, which adds flavor rather than actionable 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?

Given the output schema exists and both parameters are optional, the description covers the necessary behaviors: file creation, idempotency, project detection, and the non-git marker side effect. Nothing required to invoke the tool correctly 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 coverage is 0%, so the description must compensate, and it fully does. It explains that project is optional with a fallback detection chain (git remote, marker file, folder name), and that include_claude adds a CLAUDE.md for Claude Code.

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 by naming the tool role (initialization, first call on each terminal) and specifies the two concrete artifacts it creates: AGENTS.md and a shared announcement file. This clearly distinguishes init_bulletin from the operational sibling tools like send_note or get_board.

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 an explicit trigger (first call when a terminal connects to the mailbox) and explicitly reassures repeated use because the operation is idempotent. It does not name excluded cases or compare with alternatives, but none of the sibling tools overlap with this setup role.

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 disclosure burden. It explicitly discloses persistence ('会被保留和累积，不随认领表滚动清理'), visibility via get_board, and traceability via agent/timestamp. These go beyond the schema; only minor operational details like duplicate/overwrite behavior are absent.

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 front-loaded with purpose, then retention behavior, then parameter guidance, with bullet-style parameter lines. It is not padded and each section adds value. Minor redundancy with the schema list is acceptable because it adds usage guidance.

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 append tool, the core behavior and the two required parameters are well covered, and output schema exists so return details needn't be described. However, the project parameter is entirely undocumented both in schema and description, and no explicit 'when not to use' boundary is given. This leaves a small but real 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 0%, so the description must document parameters. It explains agent ('要和认领时一致') and decision format ('一句话讲清楚定了什么、为什么'), but says nothing about the optional project parameter. Since one of three parameters remains undefined, compensation is incomplete.

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 opens with '写决策：往共享决策区追加一条约定' and states visibility via get_board. It lists concrete use cases (定协议、记方案取舍、留踩坑结论), which distinguishes it from sibling note/claim tools. This is a specific verb+resource with clear 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 says '用于定协议、记方案取舍、留踩坑结论——凡是"需要别人看见并遵守"的内容', giving clear context. It does not explicitly name alternatives like send_note or state when not to use it, but the category '需要别人看见并遵守' implies the boundary.

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 discloses unread-cursor semantics via peek, pagination behavior via limit, and inbox/outbox content differences. However, it does not explicitly state the side effect of a normal (non-peek) read beyond implying the cursor advances.

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 compact, front-loaded with the core purpose, and organizes parameter details in a scannable list. Every line adds useful information without repetition.

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 most operational behavior and parameter semantics, and an output schema exists to describe return values. The main missing piece is the project parameter, which prevents full completeness for a 5-parameter tool with minimal schema descriptions.

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 parameters. It explains agent, box, limit, and peek with meaningful detail. The project parameter is left undocumented, leaving one gap in an otherwise strong parameter explanation.

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 clear verb and resource: read directed messages in inbox/outbox. It distinguishes itself from get_board, which auto-displays unread messages and marks them delivered, making the tool's role 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?

The description explicitly states when to use this tool instead of get_board: for reviewing history, confirming no missed messages, and checking receipts on sent messages. This gives an agent concrete routing guidance among siblings.

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 discloses the mutation effect (marks claims cancelled, releases files), the restriction to in-progress claims only, and TTL-related expiration behavior. It does not mention permissions or permanence, but the key operational boundaries are well covered.

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 short sentences, each serving a distinct purpose: main action, use cases, constraint, and TTL edge case. It is front-loaded with the core behavior and contains no filler or redundant restatement.

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 that an output schema exists, the description does not need to explain return values. It adequately covers the operation, when to use it, and the main edge cases. The primary gap is explicit parameter semantics, but overall an agent can infer the correct invocation context from the operational description.

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

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

Schema description coverage is 0%, so the description needed to compensate for the bare input schema. It only loosely refers to '某个终端' (a terminal), which maps weakly to the agent parameter, and it never explains the optional project parameter or how the parameters relate to the cancellation scope. This is insufficient given the complete lack of schema 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 the specific action '取消认领' and states that it marks all in-progress claims for a terminal as cancelled and releases files. This is a concrete verb+resource+scope statement that clearly differentiates the tool from siblings like claim_files and report_done.

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 lists when to use the tool: task cancelled, terminal offline, or claim stuck. It also provides negative guidance: reported/cancelled claims are unaffected, and expired claims do not need cancellation because the tool will prompt. However, it does not explicitly name alternative sibling tools or contrast them.

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?

There are no annotations to carry the safety or side-effect profile, so the description takes full responsibility. It explicitly discloses three side effects, including that file claims get released, history is pruned to MAX_HISTORY, and conflict checking is non-blocking (reminds but does not block). It also discloses TTL expiration behavior. This is high-quality behavioral 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 compact and well-structured: a one-line summary, a numbered list of effects, an edge-case condition, and parameter clarifications. Every sentence contributes useful information, and the most important behavioral details are 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?

For a tool with three side effects, an edge case, and no annotations, the description covers the essential behavioral and parameter context quite thoroughly. An output schema exists for return values, so that is not needed here. The only notable gap is the undocumented project parameter, which keeps this from being fully 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 schema provides no descriptions (0% coverage), so the description must compensate. It explains agent (must match the claim), summary (what was done/result), and files (comma-separated, recommended for conflict checking). However, the project parameter is not explained, leaving one of four parameters undocumented.

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 names a specific action (reporting task completion) and enumerates three concrete effects: marking a claim as reported, appending a history entry with automatic pruning, and checking for conflicting changes. This clearly differentiates it from siblings like release_claim or send_note, which have narrower purposes.

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 context is clear: this is the tool to call when claimed work is finished. It also gives a conditional rule—if the claim has expired, re-run claim_files first—which helps an agent decide when not to call it directly. It does not explicitly name alternative tools or exclusion cases, but the usage scenario is strongly implied and actionable.

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 discloses when recipients receive the message (via get_board or read_notes), that it lands in an inbox with unread count and receipt, and that request_id makes retries idempotent (same sender/id/content returns original message, no duplicate). This is substantial behavioral context beyond 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?

The description is front-loaded with purpose and use cases before parameter details, uses compact section labels, and includes examples only where they add value. There is no filler or redundant restatement.

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 6-parameter messaging tool with no annotations and an output schema present, the description thoroughly covers delivery behavior, idempotency, and almost all parameter semantics. The only gap is the undocumented 'project' parameter, so it is nearly 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?

With 0% schema description coverage, the description documents five of six parameters with examples and constraints: agent, to (comma-separated or '*'), text, task, and request_id (idempotency). However, the 'project' parameter is entirely undocumented, which prevents a perfect score.

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

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

The description opens with '定向消息：给指定终端发一条点对点消息', specifying a clear verb, resource, and delivery semantics. It also explicitly contrasts with post_decision (广播 vs 定向), so an agent can distinguish it from the closest sibling without opening schemas.

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 names concrete use cases (派活、报缺陷、接口变更通知、要回执的协调) and explains the exact division of labor with post_decision: broadcast decisions go to shared bulletin, while directed notes go to inbox with unread count and receipt. This gives explicit when-to-use and when-not-to-use guidance.

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