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

With no annotations and no output schema, the description carries the behavioral burden and does reasonably well: it discloses the output shape (affected files, line numbers, snippets, matched patterns) and the certainty ranking scheme (high/medium/heuristic), which is genuinely useful context. It omits any prerequisites (e.g., that a diff or versions/snapshots must exist) and cost or permission profile.

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 the core action front-loaded and the output contract following. No filler, though the second sentence is a dense enumeration rather than integrated into the narrative.

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 10-parameter comparison tool with no annotations, the description covers the return contract adequately since no output schema exists, but it leaves the operational context thin: no prerequisites, no statement of what must already exist (a detected diff, valid versions/snapshots), and no relationship to the sibling diff/check tools that produce those inputs.

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 explains every parameter including the from/to aliases, versions, snapshots, project path, format enum, and sourceId filter. The description adds no parameter-level meaning beyond that, so the 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?

The description names a specific action (compare detected documentation/API changes) and resource (current project workspace files), so the purpose is unambiguous. It does not, however, differentiate itself from likely-adjacent siblings such as diff_docs or check_api, leaving the agent to infer the boundary.

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 explicit when-to-use, when-not-to-use, or named alternative. An agent can infer that this answers 'what will these changes break,' but nothing tells it whether to reach for this instead of diff_docs or check_api first.

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 detection categories and four result classifications (verified, warning, mismatch, insufficient_evidence), which is useful, but omits side-effect profile, permissions, and output format details beyond what the schema enum provides.

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 front-loaded sentences: the first states purpose, the second enumerates detection and classification 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?

The description provides adequate context for a verification tool, covering purpose, detection categories, and result statuses. However, for an 8-parameter tool with no required parameters and no output schema, it leaves gaps around parameter interactions (e.g., code vs snippet alias, project/version auto-detection) and when to prefer json vs markdown.

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 all 8 parameters. The description adds no parameter-level meaning beyond the schema, which meets the baseline of 3.

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?

Names a specific verb ('Verify') and resource ('agent/generated code against indexed OpenAPI schemas and documentation'), and the listed detection categories make its scope distinct from retrieval-oriented siblings like find_api or search_docs.

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?

Describes what the tool does but gives no explicit when-to-use guidance, prerequisites, or alternatives to sibling tools. Usage is only implied by the verb 'Verify' applied to generated code.

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 adds meaningful behavioral context: it states the diff is deterministic and ignores formatting-only changes, and it enumerates the categories of changes detected. It does not explicitly state permissions or side effects, but the comparison nature implies a read-only 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?

Two sentences, front-loaded with the core purpose and followed by a key behavioral trait. Every sentence earns its place with no redundant or filler content.

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?

No output schema exists, and the description does not explain the structure of the returned diff or the default behavior when optional version/snapshot parameters are omitted (all 8 parameters are optional). While it describes what changes are detected, it leaves key operational details 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%, so the schema already documents all 8 parameters in detail. The description mentions snapshots and versions broadly but adds no syntax, defaults, or format details beyond what the schema provides; 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 ('Compare') and resource ('documentation snapshots and versions'), and explicitly lists what it detects: added, removed, modified, and deprecated API endpoints, parameters, pitfalls, and content sections. It clearly distinguishes itself from sibling tools like get_version or search_docs, which retrieve rather than diff.

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?

Usage is implied by the purpose—comparing versions/snapshots—but there is no explicit guidance on when to use this tool versus alternatives such as get_version or search_docs, nor any mention of prerequisites or 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?

With no annotations, the description carries the full behavioral burden, yet it never says whether files are written to disk, where they land, whether existing files are overwritten, or what permissions are needed. 'Deterministically' implies reproducibility but discloses nothing about side effects or failure modes for a tool whose name promises an export.

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?

A single front-loaded sentence with no filler; the parenthetical format list is functional rather than padding. It is dense but every clause (determinism, file types, grounding sources) contributes to selection.

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 5-parameter tool with no annotations and no output schema, the description is thin: it omits output destination, side effects, and any relationship to the many sibling context-gathering tools. The responseFormat parameter hints at return shape, but the description never confirms what an agent actually receives.

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 all five parameters are already documented in the schema, making 3 the baseline. The description adds only the framing that output is 'grounded in project dependency versions', which loosely ties projectDir/docVersion together but supplies no syntax or format 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 pair ('generate and export') and a concrete resource ('agent-native documentation context files'), then enumerates the exact artifacts (AGENTS.md, CLAUDE.md, skill.md, llms.txt, docs-map.md). No sibling tool in the list produces or exports files, so it is distinguishable from the search/get/find family at a glance.

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 when-to-use or when-not-to-use guidance and no named alternative. An agent cannot tell from the description whether to reach for this versus get_implementation_context or get_documentation_map when assembling agent context. Usage is only inferable from the file-format list.

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 usefully discloses what the lookup returns (parameters, schemas, auth, error responses), and 'lookup' implies a read-only operation, but it says nothing about pagination, result limits beyond the schema default, or rate/permission behavior.

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?

A single well-packed sentence with the verb and resource front-loaded and no filler. It is appropriately sized, though the trailing enumeration of return fields makes it slightly run-on rather than crisply structured.

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 five-parameter read tool with no annotations and no output schema, the description covers the purpose and the shape of the return payload, which is the main gap to fill. It does not help with tool selection against its many siblings, so an agent still lacks the routing context needed to use it confidently.

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 does add a bit of meaning by naming the lookup modes (path, operation ID, keyword) that the 'query' parameter accepts, but it contributes nothing about method, version, format, or limit beyond what the schema already documents.

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 ('lookup') and resource ('structured OpenAPI endpoints') and enumerates the lookup keys (path, operation ID, keyword) plus what comes back (parameters, schemas, auth, error responses). It reads as API-reference-specific, which loosely separates it from search_docs, but it never explicitly names or contrasts a sibling like check_api or search_docs.

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 when-to-use, when-not-to-use, or alternative routing guidance. With overlapping siblings such as check_api, search_docs, and get_documentation_map, the agent is left to infer when find_api is the right call.

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 disclosure burden. It asserts examples are 'verified' (a useful quality signal) but says nothing about permissions, rate limits, freshness, or what 'verified' actually means; return shape is only inferable from the format param.

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?

A single well-formed sentence front-loads the verb, the resource, and the qualification 'verified, framework-specific'. Nothing is wasted and nothing is buried.

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 search tool with no output schema and no annotations, the description covers purpose but omits result behavior, ranking/relevance expectations, and sibling routing. It is minimally viable rather than 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%, so all six parameters are already documented, including the format enum, limit default, and filter examples. The description's phrase 'by task, language, framework, or target API' loosely mirrors those params but adds no syntax or format detail beyond the schema, so the 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?

The description gives a specific verb (Find) and resource (verified, framework-specific code examples) plus the scoping axes (task, language, framework, target API). This clearly distinguishes it from content-oriented siblings like search_docs or find_recipe, though it never names an alternative directly.

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?

Usage is only implied: an agent can infer it should call this when it needs a code example rather than prose docs. There is no explicit 'use this when' statement, no mention of when NOT to use it, and no routing to find_recipe/find_api despite those close 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 behavioral burden. It lists the kinds of content returned but does not disclose whether the search is read-only (implied but not stated), how results are ranked, whether pagination applies, or what happens on no match. For a search tool with zero annotation coverage, this is a significant gap.

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?

A single, front-loaded sentence that efficiently enumerates the content scope. No redundant or filler language.

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 has 5 parameters, 100% schema coverage, and no output schema. The description covers the purpose and content types but omits usage context, behavioral traits, and return format expectations. It is minimally viable but leaves gaps for an agent deciding between search siblings.

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 all five parameters thoroughly, including enums, defaults, and examples. The description adds no parameter-specific detail beyond the kind categories, but the baseline for high coverage is 3; the description does reinforce the kind semantics by naming the categories. A 4 reflects that the schema does the heavy lifting and the description is adequate.

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 (Search) and a clearly named resource (documented pitfalls, gotchas, deprecations, breaking changes, runtime restrictions). This distinguishes it from siblings like search_docs or find_api, which target different content types. However, it does not explicitly name those siblings or state what it is not, so it falls short of a 5.

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 guidance on when to use this tool versus search_docs, find_api, or other search siblings. The description implies usage by listing pitfall categories but offers no context, prerequisites, or alternatives.

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 hints that results are 'evidence-grounded' but never states that this is a read-only operation, where evidence comes from, or any auth/rate constraints, so the disclosure is thin for a no-annotation 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?

A single front-loaded sentence that names the action first and then details the output shape. Efficient with no filler, though its dense list makes it slightly run-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?

No output schema exists, but the description does sketch the return structure (prerequisites, ordered steps, validation), which is genuinely useful. It still omits usage context and any behavioral notes, leaving it only minimally adequate for a four-parameter 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% with four fully documented parameters, so the schema does the heavy lifting. The description adds no parameter-level detail (e.g., how 'goal' maps to recipe output), so the 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 ('Assemble') and resource ('implementation recipe') and elaborates the output structure (prerequisites, ordered steps, validation steps). It does not, however, differentiate itself from related siblings such as find_example, find_api, or get_implementation_context, so a 4 rather than a 5.

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 contains no when-to-use guidance, no prerequisites, and no mention of alternatives. With closely related siblings like find_example and get_implementation_context, the absence of routing guidance leaves 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.

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It hints at the return payload ('complete metadata and security annotations') but says nothing about permissions, error behavior for missing IDs, or what happens when both URL and ID are supplied. 'Security annotations' is vague and unexplained.

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?

A single front-loaded sentence that states the action and lookup keys immediately. No filler, though the trailing 'with complete metadata and security annotations' is somewhat vague and slightly less earned than the rest.

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 read-only retrieval tool with no output schema or annotations, the description is adequate but thin: it does not cover mutual exclusivity of url/pageId/chunkId, failure behavior, or what 'security annotations' in the payload means. It is minimum viable rather than 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%, so the schema already documents url, format, pageId, and chunkId (including enum meanings). The description only restates the 'ID or URL' idea and adds no disambiguation between pageId and chunkId or guidance on precedence. 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 (Retrieve) and resource (documentation page or contextual chunk) with the lookup keys (ID or URL). It implicitly contrasts with search_docs by emphasizing retrieval of a specific item, but never names or distinguishes itself from that sibling 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?

There is no explicit when-to-use or when-not-to-use guidance, nor any mention of alternatives like search_docs or list_sources. The reader must infer that this is a direct-lookup tool used after a search, but nothing in the text says so.

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 usefully discloses what is returned, including 'estimated token budget footprints' which helps an agent plan context budget, but says nothing about permissions, caching, rate limits, or whether the call is read-only (only implied by 'Retrieve').

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?

A single front-loaded sentence that packs the return-content list efficiently with no filler. It is well-sized for a low-complexity read tool.

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 properly enumerates the returned artifacts (map, tree, headings, token footprints), filling that gap. Only the lack of usage guidance keeps it 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?

Schema description coverage is 100%, so all three optional parameters (format, sourceId, docVersion) are already documented in the schema. The description adds no additional parameter meaning, so the 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?

States a specific verb ('Retrieve') and resource ('hierarchical documentation map, page tree, section headings'), which clearly distinguishes it from get_doc and search_docs. It does not explicitly name any sibling, so it falls short of perfect 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 gives no when-to-use or when-not-to-use guidance and never references alternatives such as search_docs or get_doc. An agent must infer that this is a navigation/orientation tool rather than a lookup 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?

No annotations exist, so the description carries the full burden. It does disclose the internal pipeline (auto dependency/version resolution, intent detection, retrieval, compilation) and the enforcement of a token budget, which is genuine behavioral context. However it omits side effects implied by the schema (auto-ingesting/indexing a URL), permission or auth needs, latency, and failure behavior, leaving significant gaps for a 9-parameter orchestrator.

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?

It is a single dense sentence with little waste, though 'High-level documentation intelligence orchestrator' is a soft, near-marketing opener. The most important outcome, the compiled recipe, lands at the end rather than being front-loaded, costing it the top mark.

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 9 optional parameters, 100% schema coverage and no output schema, the description gives an adequate account of the behavior and the nature of the result (an evidence-grounded recipe within a token budget). It does not explain how the task/goal/query aliases interact or how format selection affects output, but nothing critical for a first correct invocation 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%, so every parameter is already documented, including aliases (goal/query), format enum, and tokenBudget default. The description adds no additional meaning to any parameter. Baseline 3 is correct when the schema does all the parameter work.

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 composite verb+resource: it resolves dependencies/versions, retrieves chunks, APIs, examples and pitfalls, and compiles an evidence-grounded recipe. This distinguishes it clearly from single-purpose siblings like find_example or find_pitfall. It stops short of the 5 because it never explicitly names a sibling it replaces or differs from, though the 'orchestrator' framing implies aggregation.

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 call this versus calling find_recipe, find_api, find_example or search_docs individually, and no prerequisites or exclusions are given. The word 'orchestrator' weakly implies an all-in-one entry point, but the agent must infer that. Comparable to the MID calibration where absent when-to-use guidance earned a 2.

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 and does not meet it. It never states whether it reads package manifests only or touches the network, whether it is side-effect free, or what the 'confidence ladder' returns or how to interpret it. The mysterious 'SemVer confidence ladder' concept is introduced without explanation.

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?

A single front-loaded sentence with no padding. It is efficient, though the undefined 'confidence ladder' term costs a little clarity for the space it occupies.

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?

No annotations and no output schema, so the description must explain what resolution actually produces — and it does not. For a three-parameter tool whose whole value is a resolved version plus some notion of confidence, the return semantics and any failure behavior are 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%, so format, library and projectPath are fully documented in the schema, establishing the baseline of 3. The description's mention of 'workspace dependencies' loosely ties to projectPath but adds no syntax, defaults, or format guidance 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 and resource: inspect workspace dependencies and resolve a compatible documentation version. This is distinguishable from the sibling retrieval tools (search_docs, get_doc), though the phrase 'SemVer confidence ladder' is unexplained jargon and the description never names which sibling it complements.

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 explicit statement of when to call this versus alternatives such as get_documentation_map or search_docs. The 'inspect workspace dependencies' phrasing weakly implies a pre-step before fetching docs, but no when/when-not condition or ordering guidance is given.

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 meaningfully disclose behavior: sources are tracked deterministically in docs.lock, semantic chunks/OpenAPI endpoints/code examples/pitfalls are extracted, and providing taskContext triggers an immediate evidence-grounded recipe. It still omits network side effects of crawling external sites, permissions, rate limits, and idempotency of re-ingestion.

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 sentences, front-loaded with the core verb/resource, then behavior, then the conditional return. Dense but each sentence contributes; the taskContext payoff is placed last as a secondary mode rather than buried mid-sentence.

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 nine-parameter ingestion tool with no annotations and no output schema, the description adequately conveys what happens (crawl, index, track) and what the taskContext path returns. It is slightly thin on persistent side effects and error/permission behavior, but the core mental model is 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%, so all nine parameters are already documented and the baseline is 3. The description adds only the dual-mode framing (URL fetch vs raw content ingestion) and reinforces the taskContext conditional, without adding format, limit, or aliasing details 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?

The description gives a precise set of verbs (ingest, crawl, parse, index) and a concrete resource (documentation from URL or raw content into DocOrbit). It is unambiguously the lone ingestion/write tool among siblings like search_docs, get_doc, and list_sources, so an agent can route to it 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?

Usage is only implied by the nature of the tool; the description never states when to prefer this over search_docs/get_doc/find_* siblings, nor any prerequisites or when-not-to-use conditions. It does surface one conditional behavior (supply taskContext to trigger recipe synthesis), which is closer to behavior than 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?

No annotations are provided, so the description carries the full behavioral burden. 'List all' implies a read-only enumeration, but there is no disclosure of pagination behavior, ordering, default limit effects, or auth requirements. For a no-annotation tool this is thin.

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?

A single front-loaded sentence with no filler. It is slightly dense by enumerating four output categories, but every clause describes what gets listed.

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 listing tool with no output schema, the description adequately conveys the scope of what is returned. It omits ordering, pagination, and how the four listed categories relate to each other, which leaves modest gaps but nothing an agent would trip over before calling 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 both limit and format are already fully documented in the schema, including the default and the markdown/json distinction. The description adds no parameter meaning beyond that, so the 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 ('List') and a concrete resource set (indexed documentation sources, snapshot records, doc versions, machine-readability status). It is clearly a listing tool distinct in kind from search_docs and get_doc, though it never names or contrasts with a sibling 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?

There is no statement of when to use this vs. search_docs or get_documentation_map, and no prerequisites or exclusions. The agent must infer that this is a broad enumeration endpoint from the word 'all'.

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 disclosure burden and does usefully reveal the hybrid FTS5 ranking, symbol-aware matching, and version-filter behavior. It omits read-only confirmation, result/pagination behavior, and error conditions, so it is only moderately transparent for a no-annotation 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?

A single dense sentence with the verb and resource front-loaded and zero filler. It is slightly jargon-heavy ('hybrid FTS5 ranking') but every clause conveys real information.

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?

No output schema and no annotations, so the description must carry more weight, yet it says nothing about the shape, pagination, or ranking of results returned. With 5 fully-documented params the basics are covered, but return-side behavior is left to inference.

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 all five parameters (limit, query, format, library, version) are already documented in the schema. The description adds only the vague phrase 'optional version filtering,' adding no syntax or semantics beyond the structured fields, 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 (Search) and resource (documentation chunks) plus the ranking mechanism. However it does not differentiate itself from the many specialized sibling search tools (find_api, find_example, find_pitfall, find_recipe), leaving the agent to guess which search variant applies.

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?

No guidance on when to use this general search versus the specialized find_* siblings, nor any prerequisites. The agent must infer selection purely from names.

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