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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions outputs like affected files, line numbers, and certainty rankings, which gives some insight. However, it doesn't state whether the tool is read-only, whether it requires prior setup, or any side effects. It's adequate but not rich.

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 concise, comprising two sentences that front-load the core purpose and then list the key outputs. There is no fluff or redundancy. It could be slightly more compact but is appropriately sized.

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 9 parameters, all optional, and no output schema. The description lists the types of results (affected files, line numbers, etc.), which partially compensates for the lack of an output schema. However, it doesn't mention any prerequisites, limitations, or the safety profile (read-only vs. side effects). Given the complexity, it's complete enough for basic usage but leaves some 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?

Schema description coverage is 100%, so all 9 parameters are documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides. Per the baseline rule, this scores a 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?

The description clearly states the tool's function: comparing detected documentation/API changes against workspace files and identifying affected files, line numbers, snippets, patterns, and certainty rankings. It uses a specific verb and resource, avoiding tautology. However, it doesn't explicitly differentiate from siblings like diff_docs, which might also compare changes, 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?

The description implies when to use it (when you have changes and want to know their impact on workspace files) but doesn't explicitly state alternatives or conditions for choosing this tool over siblings. There's no guidance on when not to use it or how it relates to diff_docs or get_implementation_context.

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 disclosing behavior. It mentions the types of checks performed and the possible outcomes, but does not state whether the tool has side effects, requires network access, or is read-only. The description is more transparent than a generic 'validates code,' but lacks explicit behavioral details.

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 succinct and well-structured, consisting of two sentences that cover purpose, checks, and output categories. It avoids unnecessary fluff and is easy to parse quickly. The structure is logical: first states the action, then the specifics, then the result types.

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 gives a good overview of the tool's functionality and mentions the output categories, providing some context for expected results. However, it does not describe the exact return format or whether the tool returns a detailed report, a simple status, or includes error messages. Given the absence of an output schema, a bit more detail on the return structure would be beneficial.

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?

All seven parameters have clear, descriptive text in the schema. For example, 'snippet' is noted as an alternative alias for 'code,' and 'project' is described as a workspace root for auto-resolving dependencies. The descriptions add meaningful context beyond the parameter names, making it easy for an agent to understand how to populate them.

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 specifies the tool's purpose: to verify code against indexed OpenAPI schemas and documentation, listing specific checks (invalid endpoints, wrong HTTP methods, missing parameters, etc.) and output categories (verified, warning, mismatch, insufficient_evidence). This distinguishes it from sibling tools like get_documentation_map or diff_docs, which serve different functions.

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 explains what the tool does but does not explicitly state when to use it versus alternatives. It implies usage for verification tasks, but lacks direct guidance such as 'use this when you need to validate generated code' or 'not for retrieving documentation.' An agent can infer the intended use, but explicit instructions would improve clarity.

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 does reveal that diffs are deterministic and ignore formatting-only changes, which is useful. However, it does not mention whether the tool is read-only, what the output structure looks like, or any side effects or prerequisites. This is partial disclosure; a more complete description would note the tool's non-mutating nature and return format.

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, front-loaded with the primary purpose, followed by a concise behavioral detail. There is no redundant or filler language. Every sentence 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?

Given the tool has 7 parameters and no output schema, the description should explain what the diff output looks like or how to use version vs snapshot parameters. It mentions both, but does not clarify the output format or any nuances about using versions versus snapshots. The description is adequate but not fully complete for an agent to know exactly what to expect from the call.

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?

All 7 parameters have schema descriptions with 100% coverage, so the schema already documents the parameters. The description mentions comparing versions and snapshots, which aligns with the fromVersion/toVersion and fromSnapshotId/toSnapshotId parameters, but it does not add additional meaning beyond what the schema already provides. The baseline of 3 applies since the schema covers the parameters thoroughly.

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 the tool's function: it compares documentation snapshots and versions to detect specific types of changes (added, removed, modified, deprecated) across API endpoints, parameters, pitfalls, and content sections. It also notes the deterministic output, which distinguishes it from vague 'compare' tools. The verb 'compare' and resource 'documentation snapshots and versions' are specific and unambiguous.

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

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

The description provides no guidance on when to use this tool versus the sibling tools. It does not mention alternatives, exclusions, or specific scenarios where this diffing tool is preferred over others like get_doc or search_docs. The agent is left to infer usage from the description alone.

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. It discloses determinism and grounding in dependency versions, and 'export' implies file creation. However, it does not disclose side effects such as whether it overwrites existing files, requires write permissions, or makes network calls. This is a meaningful gap for a tool that likely writes to disk.

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, well-structured sentence that front-loads the core purpose and lists the supported file types. Every element earns its place without redundancy or fluff. It is concise and immediately informative.

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 no output schema, so the description should explain what the tool returns or does beyond generation. It does not specify whether the output is written to files, returned as a string, or something else. It also omits prerequisites (e.g., whether a project directory is required) and potential failure modes. For a tool with this complexity, the description leaves notable 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?

Schema description coverage is 100%, so all four parameters are already documented in the schema. The description adds minimal extra meaning beyond that—it mentions grounding in dependency versions, which relates to projectDir, but does not elaborate on parameter interplay or defaults (e.g., default format). Since the schema handles parameter documentation, 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 clearly states the tool's purpose: it deterministically generates and exports agent-native documentation context files, explicitly listing the supported formats (AGENTS.md, CLAUDE.md, skill.md, llms.txt, docs-map.md). This specific verb+resource combination distinguishes it from siblings that fetch or search documentation, though it doesn't name 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?

The description implies when to use this tool (when you need to generate agent context files grounded in dependency versions) but does not explicitly state alternatives or conditions when not to use it. It doesn't mention that this is for creating files rather than retrieving docs, which is a clear contrast to siblings like get_documentation_map or search_docs, but that contrast is left implicit.

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 are absent, so the description carries the full burden. It usefully discloses that results include exact parameters, schemas, auth, and error responses. Yet it does not mention pagination behavior, matching semantics, or what happens when no endpoints match.

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

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

One concise sentence with no filler. The verb and resource come first, followed by the useful output facets. It is easy to scan and understand.

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

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

With no output schema, the description partially compensates by naming what the tool returns: parameters, schemas, auth, and error responses. The parameter set is modest and fully schema-documented. Missing details include the response shape and default limit behavior, but the definition is sufficient for selection and basic 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 coverage is 100%, so the baseline is 3. The description adds a meaningful extra search dimension for the query parameter by explicitly mentioning operation ID, which the schema's query description does not include. Other parameters are already well-covered by 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: lookup structured OpenAPI endpoints. It also names the search dimensions (path, operation ID, keyword), which clearly differentiates it from sibling tools like search_docs or find_example that target documentation or examples.

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

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

The description implies usage: use this when you need OpenAPI endpoint definitions. However, it does not explicitly say when to prefer it over sibling tools or when not to use it, leaving the agent to infer the decision from the resource type alone.

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 does communicate that results are verified and framework-specific, which is useful selection behavior, but it does not describe the return shape, result ordering, fallback behavior, or what fields each example contains. For a read-only lookup this is adequate but not thorough.

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 component earns its place: the resource type ('code examples'), the qualifiers ('verified, framework-specific'), and the search dimensions.

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 all five parameters fully documented in the schema and one simple required parameter, invocation mechanics are clear. However, the lack of annotations, output schema, or sibling-routing guidance leaves a moderate gap: the agent does not know what a returned example looks like or when to choose this tool over find_recipe or search_docs.

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 parameters are already individually documented and the baseline is 3. The description adds no new parameter semantics; it merely restates that searches happen by task, language, framework, or target API, which the schema already captures.

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 verb and resource ('Find ... code examples') and adds useful qualifiers ('verified, framework-specific'), so the agent can tell this returns sample code rather than documentation or API references. It does not explicitly differentiate itself from close siblings like find_recipe or find_api, so it falls just 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 prefer this tool over search_docs, find_recipe, find_api, or get_doc, and no exclusion criteria are stated. The filter list implies a search use case, but the agent must infer when this tool is the right choice among many similar 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?

The description does not disclose what the tool returns, whether it is read-only, or any side effects. Without annotations, the agent has no information about the tool's behavior beyond the basic search action.

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, concise sentence with no unnecessary words. It efficiently conveys the core purpose.

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 lacks information about the output format, return data, or any usage constraints. Given the tool's simplicity, it is still incomplete without stating what a successful search yields.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema descriptions cover all parameters, and the tool description's mention of categories aligns with the 'kind' parameter. However, the description adds no additional meaning about how parameters interact or affect results, so the value is moderate.

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 the resource (pitfalls) and the action (search), listing several categories. However, it does not differentiate from sibling tools like find_api or find_example, making the purpose somewhat generic.

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 alternatives such as search_docs or find_api. The description provides no context for selection, leaving the agent to infer use cases.

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 burden. It does disclose the output shape (prerequisites, ordered steps, validation steps) and the evidence-grounded intent, but it never states whether the tool performs side effects, requires permissions, or how it handles insufficient evidence. It isn't misleading, so this is a passable but not rich disclosure.

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. Every phrase contributes a distinct element of the recipe (evidence-grounded, prerequisites, ordered steps, validation steps), with no redundant or filler words.

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 explains the deliverable but omits usage context and exclusions, and with no output schema or annotations it does not fully substitute for them. The three parameters are covered by the schema, and the output is sketched, so the definition is minimally complete but not robust.

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 documentation covers 100% of the three parameters, so the baseline is 3. The description adds no parameter-specific semantics beyond the schema; goal, version, and projectPath are left to their own schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Assemble') and a clear resource ('implementation recipe'), and specifies the recipe's defining components (prerequisites, ordered steps, validation steps). This distinguishes it from sibling doc-lookup tools such as search_docs, find_api, and get_implementation_context, which are about retrieving rather than constructing a plan.

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 is given about when to choose this tool over siblings like find_example, find_pitfall, or get_implementation_context. The description states the function but not the conditions, triggers, or exclusions, leaving the agent to guess situational fit.

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 transparency burden. It does disclose a meaningful behavioral trait: the response includes complete metadata and security annotations. It does not, however, describe error behavior, what happens if no identifier is supplied, whether url/pageId/chunkId are mutually exclusive, or any access requirements.

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

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

One focused sentence with no filler; it front-loads the action and resource and adds useful output context (metadata and security annotations) 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?

The description is adequate for a straightforward lookup when the agent already has an identifier, but the lack of an output schema and the absence of any note that exactly one of url/pageId/chunkId should be supplied leaves room for misuse. It could be more complete for a tool whose parameters are all optional.

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 baseline is 3; the schema already explains url, pageId, and chunkId. The description adds the general 'by ID or URL' concept but no additional parameter-level meaning such as precedence or exclusivity.

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 ('Retrieve') and a specific resource ('documentation page or contextual chunk'), and clarifies that lookup can be by ID or URL and returns metadata and security annotations. It clearly distinguishes this from search/find/diff-style siblings, though it does not explicitly name a sibling for 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 phrase 'by ID or URL' implies the tool is intended for known-identifier lookups, which is the main selection cue. However, it provides no explicit when-to-use guidance or contrast with alternatives like search_docs or get_implementation_context, leaving the agent to infer context from the tool name and wording.

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 must carry the behavioral burden. 'Retrieve' suggests a read-only operation, and listing the expected outputs adds some transparency, but it does not mention effects, filtering semantics, or any operational caveats.

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 captures the primary purpose and expected outputs without wasted words. It is easy to scan and directly actionable.

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 tool with two optional parameters and no required inputs, the description covers the key return concepts. It could be stronger with usage guidance or examples, but the listed outputs are sufficient for an agent to understand what this tool provides.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters are documented in the schema. The tool description adds no extra meaning about how sourceId or docVersion influence the result, but the schema already supplies adequate baseline semantics.

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 specifies a concrete verb ('Retrieve') with a clear resource (the hierarchical documentation map) and lists distinct output components (page tree, section headings, token budget footprints). It is easily distinguishable from siblings like get_doc 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?

No explicit guidance is given about when to use this tool versus alternatives such as get_doc or list_sources. The description implies an overview/structural use case, but it never states conditions or exclusions, leaving the agent to infer the appropriate context.

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. It discloses that it resolves dependencies, detects intent, and operates within a token budget, but omits the side effect of auto-ingesting URLs (mentioned in the URL param schema) and doesn't clarify whether it performs any writes or has rate limits. It's not contradictory but incomplete for a tool with no annotation safety 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?

A single dense sentence packs many actions but remains readable and is front-loaded with 'orchestrator' to set context. It could be split into clearer sentences but contains no fluff or wasted words.

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 8 optional parameters and no output schema, the description is vague about the return format ('recipe' is undefined) and about how to choose this vs specialized siblings. It lacks guidance on behavior when no task is provided, how token budget affects output, and what distinguishes it from find_recipe. This is inadequate for an orchestrator of this complexity.

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 parameters are documented. The description adds context about resolving workspace dependencies and versions, but doesn't explain parameter relationships (e.g., how 'task' and 'goal' aliases interact) beyond what the schema already states. It adds minimal value over 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 clearly states it's a 'High-level documentation intelligence orchestrator' that resolves dependencies, detects intent, retrieves chunks/APIs/examples/pitfalls, and compiles a recipe. This is a specific verb+resource with a clear function, but it doesn't explicitly differentiate itself from siblings like find_recipe or search_docs, so the agent may not know when this is the right entry point over more specialized tools.

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

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

The description implies it's the high-level entry point ('orchestrator') but provides no explicit when-to-use or when-not-to-use guidance. It doesn't mention alternatives or conditions for choosing this over siblings like find_api or find_example. Usage is only implied by the 'high-level' designation.

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 full behavioral disclosure burden. It says the tool inspects the workspace and uses a 'SemVer confidence ladder' to resolve a version, but it never explains what that ladder is, whether the operation is read-only, what happens when no version is found, or what the returned value looks like.

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 compact sentence with no filler, and the key outcome—resolving a compatible version—is presented up front. The main drawback is that the dense 'SemVer confidence ladder' phrase sacrifices clarity for brevity.

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

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

With no output schema and no annotations, the description should explain the output format, failure behavior, and the meaning of the confidence ladder. It does none of these, and it also fails to position the tool among 15 doc-related siblings, leaving an agent to infer prerequisites and expected results.

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 baseline is 3. The description's reference to 'workspace dependencies' aligns with projectPath, and while it adds no new parameter-level detail, none is strictly necessary given the schema already defines both parameters clearly.

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 identifies a specific action—inspect workspace dependencies and resolve a compatible documentation version—which matches the tool name and distinguishes it from content-oriented siblings like get_doc or search_docs. The phrase 'SemVer confidence ladder' is unexplained jargon, which slightly blurs the purpose but does not hide the core action.

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 is given on when to prefer get_version over sibling tools such as search_docs, get_doc, or check_api. The description implies it should be used when version resolution is needed, but it provides no explicit conditions, exclusions, or alternative 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, the description carries the full behavioral disclosure burden, and it does a solid job: it discloses crawling, parsing, indexing, extraction of specific content types, and conditional synthesis of an implementation recipe when taskContext is provided. It stops short of a full picture by not stating what the tool returns when taskContext is absent, nor what happens on crawl failures or whether ingestion overwrites existing indexed content.

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 contain no filler: the first packs the core action, the second lists extracted artifacts and the conditional recipe pathway. The most important information is front-loaded, and the structure allows an agent to grasp purpose and behavior quickly.

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 tool with no output schema and no annotations, the description conveys the main workflow and the taskContext branch well. However, it leaves important gaps: the default return outcome when taskContext is omitted is unspecified, and there is no mention of error conditions, time cost of crawling, or how ingestion interacts with existing sources in DocOrbit.

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?

All six parameters are described in the schema (100% coverage), so the baseline is 3. The description adds marginal parameter-level value by echoing 'any URL or raw content' for url/content and by adding 'exact code and API details' to the taskContext behavior, but it mostly reinforces what the schema already states rather than introducing new parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with specific verbs ('Ingest, crawl, parse, and index authoritative documentation... into DocOrbit') and names the resource and action precisely. It clearly differentiates this ingestion/write action from read-focused siblings like search_docs and get_doc by enumerating distinct artifacts it produces: semantic chunks, OpenAPI endpoints, code examples, and pitfalls.

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 purpose implies when to use the tool—when authoritative docs need to be added to DocOrbit—but it does not explicitly state when to prefer it over alternatives or provide exclusions. No sibling tools are named, and the relationship to tools like list_sources or find_api is left unstated, so the agent must infer routing from the tool name and general purpose.

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 burden of behavioral disclosure. It communicates a read-only listing action and the scope of results, but it does not describe the output format, pagination behavior, or any limitations beyond the listed items.

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 concise sentence that front-loads the action and resource before enumerating the result contents. There is no filler or redundant wording.

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 simple list tool with one optional parameter, the description covers the core purpose and result scope. However, without an output schema or annotations, it leaves the precise return structure and any pagination behavior implicit, and it offers no guidance relative to sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully documents the only parameter, 'limit', including its type and default. The description adds no additional meaning about the parameter, such as how the limit applies to the multiple output categories.

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 identifies the action ('List') and the resource ('indexed documentation sources, snapshot records, doc versions, and machine-readability status'). It is specific enough to distinguish itself from search/get tools, though it bundles several output categories into one sentence without explicit differentiation from a tool like get_documentation_map.

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 phrase 'List all indexed...' implies this is the tool for enumerating available sources rather than searching or retrieving content. However, the description does not explicitly state when to prefer this tool over siblings like search_docs or get_doc, nor does it mention any exclusions.

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

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

With no annotations, the description carries the full burden, and it does add meaningful behavioral context by revealing the hybrid FTS5 ranking and symbol awareness. However, it does not disclose what the result looks like, whether it is read-only, or any limits beyond the schema's default limit, leaving some behavior implicit.

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 packs the core purpose and key capabilities with no filler. The most important action ('Search documentation chunks') comes first, followed by differentiating details.

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

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

The description is adequate for a straightforward search tool, but the lack of an output schema and the presence of many closely related siblings mean more context could help an agent decide correctly. It does not mention result format, default behavior beyond the schema, or how it relates to the specialized find_* tools.

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's mention of 'version filtering' mirrors the version parameter and 'symbol awareness' aligns with the query parameter's existing 'code symbol' wording, but it adds no new parameter-level meaning 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?

The description uses a specific verb ('Search') with a clear resource ('documentation chunks') and adds distinguishing technical features (hybrid FTS5 ranking, symbol awareness, version filtering). This makes the tool's role obvious and separates it from the more targeted find_* siblings without needing to open 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?

The description gives no guidance on when to use this tool versus the many siblings like find_api, find_example, or get_doc. It states capabilities but does not explain when a general chunk search is preferred over a specialized lookup or provide exclusions.

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