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

With no annotations, the description carries the behavioral burden and does well: it discloses the return shape (deleted metadata with deleted=True) and the failure mode (raises if no output has that id). It does not explicitly call out irreversibility or auth requirements, but the destructive nature and error contract are clear.

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 short sentences, front-loaded with the core action, then return value, then error behavior. No wasted words and the id-discovery hint arrives exactly where needed.

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 mutation with an output schema, everything an agent needs is present: the action, how to source the id, the success return, and the failure condition. Nothing material 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% and the single parameter already documents its type and provenance (from list_outputs_tool). The description only restates 'by id', adding no syntax or format detail beyond the schema, 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 (Delete), resource (saved report output), and scope (one, by id), which cleanly distinguishes it from list_outputs_tool and prune_outputs_tool. An agent knows exactly what operation this performs 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?

Directs the agent to list_outputs_tool for obtaining ids, giving a clear prerequisite workflow. It does not explicitly mention the bulk-delete alternative (prune_outputs_tool) or state when-not to use this tool, so it stops short of full sibling routing.

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 burden. It discloses the default behavior (most recent output), the date-specific behavior, and the fallback semantics of 'latest output gathered on a specific date.' This is meaningful behavioral context beyond what the schema expresses, though it does not cover edge cases like missing outputs.

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 main purpose appears in the first sentence, and the only additional sentence explains the optional parameter behavior. Every sentence earns its place with no 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?

For a low-complexity read tool, the description is complete: it states the resource, the default behavior, the optional date behavior, and the parameters are fully covered by the schema. An output schema exists, so return-value details are already provided elsewhere, and no critical invocation detail 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 are already well described in the schema, so the baseline is 3. The description adds context by explaining the default selection behavior and how gathered_date changes the result, but it does not significantly expand on the parameter meanings 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 clearly states a specific verb ('Read') and resource ('gathered report output'), and it adds the purpose ('for compiling a report'). It also distinguishes this tool from siblings by clarifying it retrieves outputs, whereas list_reports_tool, get_spec_tool, and save_output_tool imply different 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 usage context is implied by the phrase 'for compiling a report' and by the optional date parameter, but there is no explicit guidance on when to choose this tool over alternatives. It does not describe exclusions or mention sibling tools, so the agent must infer the appropriate moment to call 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 of behavioral disclosure. It clarifies what the return payload contains (prompt + source config) and the invocation context, but it does not explicitly state that the operation is read-only, what happens for unknown report names, or any auth requirements. 'Return' implies a safe read, but it is not explicit.

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 core action and resource; the second adds valuable contextual information about the caller. Every word 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?

For a one-parameter read tool with an existing output schema, the description provides enough to invoke it correctly: what it returns and when to use it. Minor gaps such as not-found behavior or explicit read-only assurance are acceptable for a simple getter, but would make it more 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 input schema already provides 100% coverage for the single 'name' parameter, including an example. The description adds only a slight restatement ('named report') and does not provide additional semantic depth such as naming conventions, validation rules, or behavior for missing names.

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 'Return' with a clear resource: 'gather spec (prompt + source config) for a report definition.' The second sentence adds a concrete invocation context (autonomous gatherer callback), which makes its distinct role relative to sibling tools obvious.

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 clearly states when this tool is used: the autonomous gatherer calls it on callback to learn what to collect for the named report. It does not explicitly mention alternatives or exclusions, but the callback context is strong enough to guide an agent without ambiguity.

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 and does meaningful work: it discloses that the records are pre-computed and stored on the run (not fetched live at call time) and that filtering already happened in code, which tells the agent why the results are compact/limited. It says nothing about permissions, error behavior, or freshness beyond that, so not a 5.

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 core action is front-loaded in the first sentence, and the remaining sentences explain the domain model and the call pattern without obvious filler. Slightly dense for a five-parameter read tool, but every sentence carries information an agent needs.

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?

An output schema exists, so return values need not be explained, and the description covers what the index contains and how paging works. It leaves minor gaps around pagination boundaries and what happens when a section name is invalid, which keeps it from a 5.

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, but the description adds real semantics to the optional `section` parameter by explaining that omitting it returns the index (window, overall status, per-section counts and errors) and that sections are then paged individually. That index/section interaction is not derivable from the schema 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?

States a specific verb and resource ("Read the pre-gathered sweep for a run") and then defines what a sweep actually is — reports gathered by Metsuke before the gatherer is called, with fixed source calls, reply-state checks and noise filters run in code. That domain framing lets an agent distinguish this clearly from siblings like get_output_tool or list_reports_tool without opening either 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?

Gives an explicit workflow: "Call with no section for the index... then page through each section you need." The two-step discovery-then-paginate pattern is clear and actionable. It stops short of naming when to prefer an alternative tool or a when-not condition, so it is not a full 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 provided, the description carries the disclosure burden, and it does well: it reveals that results are lightweight one-row-per-run entries, that payloads are deliberately excluded to keep browsing cheap, and enumerates the returned fields. It is silent on auth or rate-limit behavior, which keeps it out of 5 territory.

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, front-loaded with the purpose and ordering, followed by the payload-exclusion rationale and sibling routing. Every clause earns its place and nothing is redundant.

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 tool is a simple two-parameter read and an output schema exists, so return values need no expansion. The description covers purpose, cost rationale, and sibling routing, leaving only minor gaps such as pagination behavior for large histories.

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 (limit, report_name) are fully documented in the schema, so the baseline is 3. The description adds no parameter-specific detail (no syntax, defaults, or filtering semantics) beyond what the schema already states.

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 ('List saved report outputs (the run history)') plus ordering ('newest first'), and explicitly contrasts itself with get_output_tool, delete_output_tool, and prune_outputs_tool. An agent can distinguish this browse-the-history tool from siblings 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?

It routes the agent explicitly: use get_output_tool to pull one run's findings, and delete_output_tool / prune_outputs_tool to prune. That gives clear selection criteria against the closest alternatives, though it does not state an explicit 'when not to use this' condition or any prerequisite/permission requirement.

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, so the description carries the behavioral burden. It clearly states this is a listing operation that 'returns each definition' with specific fields, implying a non-mutating read behavior. It does not mention edge cases or pagination, but for a simple list tool this is adequate.

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 short sentences with no filler. The core purpose is front-loaded in the first sentence, and the second sentence efficiently enumerates the return fields.

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 zero parameters, an output schema present, and a clear statement of purpose and returned fields, the description fully supports correct invocation and selection. 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?

The tool has zero parameters, so the baseline is 4. The description reinforces that it lists 'all' definitions and returns each one, making it clear there are no filters or arguments required.

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 action ('List all report definitions') and a specific resource ('the catalog'), making the tool's function clear. It does not explicitly mention sibling tools, but the 'all' scope and report-definition focus distinguish it from the get/save/upsert siblings.

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 intended use is implied: use it when you need to enumerate all report definitions in the catalog. However, it does not explicitly state when not to use it or how it relates to alternatives like get_spec_tool or get_output_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, the description carries the full behavioral burden. It discloses what gets destroyed and the precise deletion conditions (keep_last=0 deletes all, before_date is strict), but says nothing about irreversibility, required permissions, or whether a confirmation is expected for a destructive bulk operation.

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?

Front-loaded with the action and result, followed by a compact criteria explanation with no filler. The 'Returns the count and ids deleted' line is mild overlap with the existing output schema, but it is a single clause and reads well at a glance.

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?

An output schema exists so return values need not be detailed, and the description covers the prune semantics and criteria exclusivity adequately for a 3-param destructive tool. Remaining gaps are the lack of any permission/irreversibility note, which would matter for a bulk delete.

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 baseline is 3, but the description adds genuine meaning beyond the schema: the two criteria are mutually exclusive (use exactly one) and keep_last=0 has the special meaning of deleting everything. It also clarifies strictness of before_date, which the schema does not convey.

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 (bulk-prune) and resource (a report's saved outputs), with the 'bulk' scope implicitly distinguishing it from the singular delete_output_tool sibling. An agent can tell it apart from delete_output_tool and save_output_tool 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?

Explicitly requires 'exactly one criterion' and explains both options (keep_last, before_date), which is real selection guidance. It does not, however, name an alternative tool or state when a caller should prefer delete_output_tool or list_outputs_tool instead, so it stops short of full routing 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, the description carries the full burden and does disclose meaningful behavior: one row per fire, that omitting run_id still produces a fresh run identity ('Metsuke stamps a fresh run identity either way'), and that findings should carry source URLs for downstream citation. It omits idempotency/duplicate handling and permission requirements, which keeps it from a 5.

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?

Front-loads purpose in the first sentence, then layers usage detail. Four sentences, each earning its place, though domain jargon ('fire callback', 'Metsuke') assumes shared context and slightly reduces standalone clarity.

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?

An output schema exists, so return-value explanation is unnecessary, and the description correctly focuses on the input-side lifecycle: run_id provenance, payload expectations, and the two save modes. Adequate for a mutation tool of this complexity, with only minor gaps around failure/duplicate behavior.

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 mildly enriches run_id semantics ('one row per fire', completes 'that exact in-flight run') and reiterates the source_url expectation, but adds little beyond what the schema descriptions already document for each field.

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?

Opens with a specific verb+resource: 'Persist a gathered report output', and immediately clarifies its transactional role ('completing the run that opened it'). This clearly positions it as the write path, distinguishing it from read-oriented siblings like get_output_tool, list_outputs_tool, and delete_output_tool.

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?

Gives explicit timing ('The gatherer writes findings here after sweeping the sources') and two distinct invocation modes: pass run_id from the fire callback to complete an in-flight run, or omit it for an ad-hoc save. It stops short of naming sibling alternatives (e.g., get_output_tool) to route away from, but the when-to-use context is clear.

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 the external callback chain (Metsuke POSTs to the Trentina alert endpoint, forwarded to the owning gatherer) and the configuration prerequisites (TRENTINA_ALERT_URL + METSUKE_ALERT_TOKEN). It does not say whether the call blocks until the gather finishes, nor what happens on failure when the callback is unconfigured.

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, front-loaded with the imperative action, then mechanism, then prerequisite. The middle sentence on the alert endpoint is somewhat internal but earns its place as behavioral context; overall tight.

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?

An output schema exists, so return values need no explanation, and the prerequisites and side-effect path are stated. The main remaining gap is the synchronous/asynchronous nature of the trigger and error behavior, but for a one-parameter tool this is largely 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?

Schema description coverage is 100% and the single parameter is documented in-schema with an example value, so the baseline is 3. The description adds no extra meaning about the name parameter 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?

States a specific verb and resource: fire a report gather immediately rather than on its schedule. The action is unambiguous and clearly distinct from the list/get/upsert/delete siblings, though it never names or contrasts them 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?

"Right now, without waiting for its schedule" gives a clear condition for selecting this tool over simply letting the scheduler run. No explicit when-not or alternative tool is named, but the triggering context is well defined.

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 must carry the behavioral burden. It usefully discloses upsert semantics, that owner_agent makes identity data rather than code (re-homing without a rebuild), and that schedule is a live cron fired by the built-in scheduler. It omits update-overwrite behavior, permission requirements, and side effects, so it adds context but not a full behavioral picture.

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 core action is front-loaded in the first sentence, followed by two tight sentences that each explain a distinct field behavior. No filler or 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?

An output schema exists, so return values need no explanation. For a six-parameter upsert mutation with no annotations, the description covers the two most conceptually important fields but leaves source_config, gather_prompt, and the update-vs-create behavioral distinction unaddressed, making it adequate but incomplete.

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 already 100%, but the description adds genuine meaning beyond it: owner_agent carries the re-homing rationale and schedule is framed as a live cron fired by Metsuke's scheduler. This enriches at least two parameters above the schema baseline, though source_config and gather_prompt remain unaddressed.

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 pair (create or update) and resource (report definition), which is clear. However it does not differentiate from siblings like list_reports_tool, trigger_report_tool, or delete_output_tool, so the agent gets a precise action but no routing contrast.

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 text explains field semantics rather than when to invoke this tool versus alternatives. There is no when-to-use, when-not-to-use, or sibling routing guidance (e.g., trigger_report_tool for firing an existing report), leaving the agent to infer selection.

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