journeyman

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false. The description adds valuable behavior beyond annotations: it returns a 404-shaped payload when the id is unknown and never fabricates a nearest match, which helps an agent understand failure semantics.

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 tight sentences with no filler. The core lookup behavior is front-loaded, and the beneficial failure-mode detail is added in the second sentence without 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?

With one well-documented parameter, an output schema present, and annotations covering safety, the description provides sufficient context. The 404 behavior and no-fabrication guarantee cover the key edge case an agent would care about when invoking this 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% for the single required 'id' parameter, including an example ('devplane-P02'). The description reinforces that the id is stable but does not add meaning beyond what the schema already provides, so 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?

The description uses a specific verb ('Lookup') and clearly identifies the resource ('a single Pattern-Assist row by stable id'). It also differentiates this tool from siblings like list_patterns and search_patterns by emphasizing single-row, id-based lookup.

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 implies this tool is for retrieving a specific row when the stable id is known, versus listing or searching. It does not explicitly name alternatives or state when not to use it, but the intended use context is unambiguous.

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 indicate readOnlyHint=true and destructiveHint=false, so the safety profile is established. The description adds that results are paginated and limited to ids and summaries, but does not disclose ordering, filtering behavior, or pagination defaults, which are relevant 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 a single focused sentence with no wasted words. The key information—paginated, pattern ids and summaries, vendored corpus—is front-loaded and sufficient for a first-pass understanding.

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?

Basic invocation is clear, and the output schema plus annotations cover return shape and safety. However, the optional filtering parameters are left unexplained, and there is no guidance about pagination behavior or how this listing relates to the sibling search tool, leaving some gaps for an agent deciding how to query.

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 carries the burden of explaining parameters, but it only hints at limit/offset through 'paginated.' The area and provenance filters are not mentioned at all, and no additional meaning is added to the parameter names beyond what the schema already shows.

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 action ('Paginated inventory') and a specific resource ('pattern ids and summaries from the vendored corpus'). This distinguishes it from siblings like get_pattern (single item), search_patterns (searching), and list_public_pages (public pages).

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 conveys that this is the tool for enumerating all vendored corpus patterns, but it does not explicitly say when to prefer it over search_patterns or get_pattern. Usage context is implied by 'inventory' and 'paginated', but no alternative routing or exclusion conditions are stated.

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 destructiveHint=false; the description adds useful scope and content context by specifying that the result is a site map of canonical human-pages and REST/MCP endpoints confined to 'this host.' It does not overpromise side effects, and there is no contradiction with 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 a single front-loaded sentence with no filler. Every phrase adds meaning: audience ('agents'), resource type ('canonical human pages'), endpoint type ('read-only REST/MCP endpoints'), and scope ('on this host').

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 zero-parameter read-only list role, the output schema, and the safety annotations, the description provides enough context for correct invocation. It clarifies what will be returned (pages and endpoints) and where (this host), leaving no significant operational gaps.

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?

There are zero parameters and schema coverage is 100%, so the schema is complete. Per the 0-parameter baseline, the description needs no additional parameter guidance, and the no-arguments call is self-evident from the empty input 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?

The description names a concrete resource—'canonical human pages plus read-only REST/MCP endpoints on this host'—with a clear listing verb and host scope. This distinguishes it from sibling pattern tools (get_pattern, list_patterns, search_patterns) by content domain (pages/endpoints vs patterns).

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?

'Site map for agents' implies this is the discovery/orientation tool, which gives context for when to call it. However, it never explicitly says when to use this over list_patterns/search_patterns or when not to use it, so an agent must infer the boundary from the tool name and sibling names.

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 destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail about the response structure: each hit carries a corpus why, a when-not/FTO trade-off, and cited same-area cross-links. This goes beyond the annotations without contradicting them.

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 sentences with no filler. The core purpose is front-loaded, and the usage condition is stated immediately after, making it easy for an agent to scan and act on.

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 two-parameter, read-only tool with an output schema, the description is complete. It covers what the tool does, what results look like, and when to use it. The 'C-03' code is slightly opaque but does not block 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 query and limit parameters are already documented in the schema. The description does not add parameter-level detail beyond confirming that the query is a 'task or problem to recommend against,' which is also in the schema. 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 and resource: 'ranked Pattern-Assist recommendations for a task.' It also distinguishes itself from a lexical hit list, making clear it is a recommendation tool rather than a plain search tool. The description of hit components reinforces the tool's identity.

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 says to use this tool 'when the learner wants alternatives, not just a lexical hit list,' which gives clear usage context. It does not name the sibling tool (likely search_patterns) explicitly, but the contrast is strong enough to route an agent correctly.

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 read-only and non-destructive behavior, and the description adds meaningful behavioral detail beyond that: hybrid lexical/embedding search with lexical fallback and the presence of ranked results with citations. It does not over-promise or contradict 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?

Three short sentences carry distinct, non-redundant information: what is searched, what is returned, and when to use it. The operation is front-loaded and there is no 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?

With full schema coverage, safety annotations, and a present output schema, the description covers operation mechanics, result content, and a usage cue. It is nearly complete, but it does not help the agent choose between search_patterns and the very similar recommendation/list siblings, leaving some contextual 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 100%, so the schema already documents each parameter, which sets a baseline of 3. The description reinforces that the query targets a corpus and results are ranked, but it adds no parameter-specific meaning beyond the input 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?

The description states a specific verb and resource ('Search the vendored Pattern-Assist corpus') and clarifies what the tool returns (ranked patterns with source_ref citations and optional when_not guidance). It is clearly distinct in practice from get_pattern and list_patterns, though it never names a sibling or states the contrast 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?

'Use this before asserting an approach' gives a clear, directive context for when to invoke the tool. It does not mention when not to use it, nor does it point to alternatives such as list_patterns or recommend_patterns, so it stops short of full exclusion guidance.

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