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

Annotations already indicate readOnlyHint=true, so the safety profile is known. The description adds meaningful behavioral detail beyond that: it documents the return contents and explains that supplying optional identifiers triggers disclosure verification instead of deferring to manual review. This gives an agent a good sense of what will happen when it invokes the tool.

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: the first sentence states the core action, the second explains the output, and the third clarifies the optional-parameter behavior. No sentence is wasted.

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 high schema coverage, the presence of an output schema, and read-only annotations, the description covers the essential invocation context well. It explains what results look like and how optional context improves the check, though it could additionally mention how this tool relates to get_receipt or when a previously generated receipt should be used instead.

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 all six parameters are already documented. The description adds value by explaining the functional impact of the optional identifiers—brokerage, licensee, and license_id—enabling verification of disclosure elements rather than deferring them. This goes beyond the schema's individual parameter 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—'Run listing text through the compliance rule engine'—and then distinguishes the tool by explaining it returns fired rules, the statute behind each, and missing required elements. This clearly differentiates it from siblings like explain_rule and suggest_rewrite.

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: use this when you need to check listing text against the compliance rule engine before publication. It also explains how adding brokerage, licensee, and license_id affects the check, though it does not explicitly contrast with sibling tools or state when not to use 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?

Annotations already mark the tool read-only and closed-world. The description adds value by specifying that it returns the full rule and the statute, and importantly warns to use the `authority` field as the citation rather than substituting a remembered one. This gives behavioral guidance beyond the structured annotations.

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

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

The description is three short sentences, front-loaded with the main purpose and followed by a use case and a caveat. Every sentence carries necessary information; no fluff or redundancy.

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

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

For a one-parameter, read-only tool with an output schema, the description covers the purpose, the trigger for use, and the critical caveat about the authority field. The runtime context (finding IDs, rule IDs) is referenced in the schema. Nothing essential is missing 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 single parameter `rule_id` is fully documented in the schema (100% coverage) with a clear description and example. The tool description does not add anything about the parameter, so the schema 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 opens with a specific action and object: 'Return the full rule behind a finding, including the statute it rests on.' This clearly states the tool's function and scope, and the second sentence adds the use context (before explaining why text was flagged). It does not explicitly name or contrast sibling tools, so it stops short of full differentiation.

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

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

The description explicitly instructs when to use the tool: 'Use this before telling anyone why their text was flagged.' This is clear contextual guidance. No exclusions or alternative routing is provided, but the context is enough to avoid misuse 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?

Beyond the readOnlyHint and openWorldHint annotations, the description explains what a receipt records, the SHA-256 digest, and the anchoring ledger property. It also discloses conditional behavior ('if one exists') and the trust rationale, which are meaningful details not present in the annotations.

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

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

The main action is front-loaded in the first sentence, and the following sentences add relevant context about receipt contents and anchoring without fluff. Every sentence earns its place, and the length is appropriate for the conceptual complexity.

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 one-parameter read-only tool with an output schema, the description covers the tool's semantics, return contents, and an important edge case (anchor absent). There is no obvious invocation gap, and the description is complete enough 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?

The schema fully documents the only parameter, receipt_id, including an example value, so schema coverage is 100%. The description adds no additional meaning about the parameter itself, keeping it at the 3 baseline.

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 sentence states a specific verb ('Retrieve') and resource ('stored check receipt'), and adds the key conditional 'including its anchoring block if one exists.' This clearly differentiates the tool from siblings like check_listing, which suggests enumeration, and explain_rule/suggest_rewrite, which are rule-focused.

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 the tool is for fetching a single receipt by ID, but it never explicitly states when to prefer it over check_listing or mentions alternatives. An agent must infer usage from the name, title, and schema rather than receiving direct when/when-not guidance.

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

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

Annotations already declare readOnlyHint=true, and the description strengthens this by explaining the tool 'does not rewrite anything' and that composing new text is the caller's job. It also reveals the postcondition: the final result must be re-checked with check_listing, which is valuable behavioral context beyond the annotations.

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

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

The description is compact and front-loaded: the first sentence states the core function, and the following sentences add essential behavioral constraints. Every sentence earns its place, with no filler or repetition of schema details.

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

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

The description covers the tool's contract, return nature (spans and substitutions), and required follow-up check. An output schema exists, so the return values do not need full explanation. The main gap is the unexplained state and channel parameters, which keeps this from being fully complete, but the overall context is strong.

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 only 33%; the text parameter is documented in the schema, but state and channel are only given defaults with no explanation. The description does not compensate for these undocumented parameters or explain their role in the rewrite brief, so an agent has to infer their meaning from names and defaults.

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 clear verb and resource: it 'collect[s] what must change in a text' via character offsets and replacement wording. It also distinguishes itself from siblings by explicitly saying it 'deliberately does not rewrite anything' and naming check_listing as the follow-up validation step.

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: this tool produces a rewrite brief, the calling model must compose the new text, and the result must be checked with check_listing before publishing. It does not explicitly catalog when to prefer this over explain_rule or get_receipt, but the sequencing and responsibility for composing the final text are clearly stated.

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