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

With no annotations, the description carries the full behavioral burden and does disclose the key side effect: the markdown is saved to data/reports/ in addition to being returned. It omits what happens on filename collisions, whether existing reports are overwritten, and any permission requirements, leaving meaningful gaps for a write-capable 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?

Two dense sentences with zero filler; the output contents are front-loaded and the return/persistence behavior is stated last where it belongs.

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, so the description usefully states both the return value (markdown) and the storage location. For a two-parameter tool with fully documented schema this is nearly complete, though it could say what the saved artifact is named or how check_report consumes it.

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 'topic' and 'sources', including the 'previously scored with fetch_and_score' constraint that the description echoes. The description adds no new parameter-level detail, so the baseline 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?

States a specific verb (assemble) and resource (report shell) and enumerates the three sections it produces: claims stubs, numbered citation registry, scoring appendix. 'Shell from already-scored sources' implicitly separates it from plan_research and fetch_and_score, but no sibling is named explicitly.

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?

'From already-scored sources' implies the prerequisite that fetch_and_score must run first, which is genuine usage context. However, there is no explicit statement of when to call this versus check_report, or what to do if sources are unscored.

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 discloses a genuinely useful trait: orphan claims come back as an error list and the tool never reports a pass, plus the dual input mode and precedence. It stops short of stating whether the operation is read-only or how a clean report is represented.

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 tight sentences with zero filler: the core behavior, including the 'never a pass' caveat, is front-loaded, and the input forms follow immediately. Every clause 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?

With no annotations and no output schema, the description does most of the required work, covering what is verified, the failure shape, and the two input routes. The notable remaining gap is that neither parameter is required, yet the description never says what happens if both report_id and report_path are omitted.

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 both parameters are already documented, including the 'overrides report_id' precedence. The description restates the accepted input forms but adds no format, syntax, or validation detail beyond the schema, so it meets the baseline rather than exceeding 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?

States a specific verb and resource: verify every substantive claim in a report cites a scored source. It clearly sits downstream of build_report and is distinguishable from plan_research, fetch_and_score, and build_report without opening any 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?

The description implies the pipeline position by accepting a 'report id (as built)' and annotating the schema with 'Report id returned by build_report', so the workflow context is inferable. However, it never states explicitly when to use this versus the sibling tools, nor any when-not condition or prerequisite.

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 it does disclose two non-obvious traits: the granular, explainable composition of the score and the side effect that results are persisted/'registered' for later use by other tools. It omits failure behavior for unreachable or paywalled URLs, crawl timeouts, and any rate limits, so it is good but not exhaustive.

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 dense sentences, front-loaded with the action and result, followed by the integration note. Every clause (score range, sub-signals, registration) carries information; nothing is redundant 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?

There is no output schema, so the description must describe returns — and it does, naming the 0-100 scale and the individual signals that make the score explainable, plus where scores go next. It is nearly complete for a simple one-parameter tool, with only error/edge-case behavior left unstated.

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 single source_url parameter is already fully documented in the schema, so the baseline of 3 applies. The description's phrase 'one source URL' only reinforces the single-URL scope; it adds no format, validation, or constraint detail beyond the 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?

States a specific verb (crawl/fetch and score) on a specific resource (one source URL) and enumerates the return payload: a 0-100 score plus primary-source, freshness, paywall and conflict-of-interest components. It also positions itself against the siblings by naming build_report/check_report as consumers of the registered scores, so an agent can tell it apart from those 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 hints at pipeline placement by noting scores are 'registered for use in build_report/check_report', which implies this runs per-source ahead of report building. However, it never states when to use it versus plan_research or how many sources to process, and gives no exclusions or prerequisites — usage is only implied.

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 usefully discloses what the tool produces (targets plus kill criteria), but says nothing about whether it is read-only, whether it persists anything, or what the returned plan looks like structurally.

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?

One dense sentence, front-loaded with the core transformation and then the payoff (kill criteria). Every clause earns its place and nothing is padded.

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, so the description is the only source of behavioral and return-value information. It hints at the plan's components but is thin for a tool whose entire value is the shape of the plan it emits.

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% for both parameters, so the schema already documents 'scope' and 'domain_hints' with examples. The description adds no syntax, format, or constraint detail beyond that, making the baseline 3 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 gives a specific verb+resource ('turn a research scope into a source-target plan') and enumerates the plan's contents (primary-source targets, corroborating targets, kill criteria). It is clearly distinct from fetch_and_score/build_report/check_report in substance, but it never names or contrasts those siblings, so the differentiation is implicit.

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 the sibling tools, nor any prerequisites (e.g. 'call before fetch_and_score'). The only conditional language ('when to abandon the topic') describes the plan's content, not the tool's usage context.

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