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

With no annotations provided, the description carries the burden of disclosing safety. The verb 'Summarize' and the phrase 'local project' imply read-only behavior, but the description does not explicitly state that it does not modify files or perform network calls. It does clarify what information is reported, which provides some behavioral context.

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

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

The description is compact and efficiently structured: a one-sentence purpose, a one-line output enumeration, and an Args section. Every sentence contributes meaningful information with no 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?

Given the presence of an output schema, the description does not need to explain return values. It covers the tool's purpose, key deliverables, and the only parameter. It could add prerequisites (e.g., path must exist) or mention that it reads only local files, but the description is largely adequate for this simple 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?

The schema provides only a 'path' string with no description (coverage 0%). The description compensates fully by explaining that 'path' is an 'absolute path to the local project directory', adding crucial semantics beyond the structured 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 the action ('Summarize the architecture') and the target ('a local project'), and lists specific outputs (file language breakdown, top-level structure, likely entry points). This distinguishes it from siblings like project_statistics or dependency_summary.

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 the tool (when an architecture overview of the local project is needed) but provides no explicit comparison to siblings such as repository_summary or explain_repository, nor any 'when not to use' 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 burden. It discloses the core actions, a prerequisite (git repo with origin), and the commit message default. However, it does not mention authentication, failure modes, or what happens if there are no committed changes. This is partial but acceptable for a simple 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?

The description is concise and front-loaded: the first sentence states the action, followed by a brief prerequisite/use-case line and a short Args list. No redundant sentences.

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 only 2 parameters and an output schema present, the description covers the main purpose, prerequisites, and parameter semantics. It omits edge-case behavior like no-op commits or remote conflicts, but given low complexity and the output schema, the description is reasonably complete.

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

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

The schema includes no property descriptions (0% coverage), but the description compensates with an Args section explaining path as an absolute directory and commit_message as optional with a dated default. It also adds the requirement that path be a git repository. This provides meaningful context beyond the bare 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 the tool's function with specific verbs 'Commit' and 'push' and names the target resource 'GitHub'. The phrase 'routine backups of an existing project' distinguishes it from sibling operations like publish_project.

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 explicitly recommends using this tool 'for routine backups of an existing project' and specifies a prerequisite (path must be a git repository with or able to create an origin remote). It does not name alternative tools or exclusions, but the context is clear.

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

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

With no annotations, the description must disclose safety and side effects, but it only says 'compare' and 'summarize.' It does not mention that it is read-only, whether it accesses network, or what kind of differences are included. This is minimal.

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: one sentence for purpose plus a clear Args section. No unnecessary words, and it is front-loaded with the primary action.

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 two-parameter tool with an output schema, the description covers the essentials. However, it lacks usage guidance and more behavioral detail, such as what kind of differences are summarized or how the comparison is performed, leaving some ambiguity in context.

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 description adds useful format guidance for each parameter ('repo' or 'owner/repo'), which the input schema does not provide. Since schema description coverage is 0%, this compensates well for both parameters.

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 'Compare two repositories and summarize their differences' with a specific verb and resource. This distinguishes it from sibling tools like repository_summary or explain_repository, which handle single repositories.

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 use this tool versus alternatives like repository_summary or explain_repository. The description only states what it does, not why or when to choose 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?

No annotations are provided, so the description carries full burden. It states the action and 'under your account' but omits details like authentication requirements, behavior on duplicate names, success/failure responses, and whether the repo is initialized with a README. This is sparse for a mutating 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?

The description is concise and front-loaded with the main purpose. The Args list is cleanly formatted and avoids extra fluff. It earns its place without being verbose.

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?

While the output schema covers return values, the description lacks context for preconditions (e.g., authentication) and potential failures (e.g., name conflicts). Given the tool's mutating nature and the presence of overlapping sibling tools, it is minimally complete but leaves 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 0%, so the description must compensate. It does: name lists allowed characters, description notes it's shown on GitHub, and private clarifies its boolean nature. This adds meaning beyond the schema's types and defaults.

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 action ('Create a new repository') and the resource ('on GitHub under your account'). It distinguishes itself from sibling tools like list_repositories and publish_project by focusing on the act of creation on GitHub.

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: use when you want to create a new GitHub repository. However, there is no explicit guidance on when to choose this over alternatives like publish_project or backup_project, and no mention of 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?

Describes core behavior (detects manifest, lists dependencies) but does not disclose behavior for multiple manifests, subdirectory traversal, or error cases; no annotations to compensate.

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?

Purpose front-loaded, concise, no redundant info.

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?

Covers the main use case and supported manifests; output schema covers return values, but missing details about scope of search (root vs recursive) and failure modes.

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?

Description explicitly defines path as absolute path to project directory, adding meaning beyond the bare schema type.

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 it summarizes dependencies of a local project and lists supported manifest types, distinguishing it from general repository summary 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?

Implies usage for local dependency analysis but does not state when not to use or name alternatives like repository_summary.

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

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states only that the tool explains a repository in plain language, but does not disclose whether it performs a read-only operation, requires authentication, accesses external services, or has any side effects. The lack of behavioral detail is a significant gap for a tool with no annotation safety net.

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 exceptionally concise: a single purpose sentence plus a parameter definition. It is front-loaded with the main action and contains no filler, repetition, or unnecessary detail. Every word earns its place.

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

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

Given the tool's simplicity (one parameter, output schema present), the description provides sufficient information to invoke the tool correctly. However, it lacks usage guidance and behavioral transparency, leaving the agent to infer when to use it and what side effects may occur. The output schema mitigates the need to describe return values, but the missing contextual elements keep this 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?

The schema provides only a string type for 'name', giving no semantic meaning. The description compensates by explaining the expected format: 'repo' or 'owner/repo'. This adds meaningful guidance that goes beyond the schema, making the one parameter clear and actionable.

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: to explain what a repository is about in plain language, using a specific verb ('explain') and resource ('repository'). However, with the sibling tool 'repository_summary' present, the description does not explicitly differentiate between the two, creating potential confusion about which tool to choose.

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 alternatives. For example, it doesn't explain how 'explain_repository' differs from 'repository_summary' or when a plain-language explanation is preferred over a structured summary. No contexts or exclusions are mentioned.

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

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

With no annotations, the description must disclose behavior, but it only explains parameters. It does not mention authentication, pagination, rate limits, or the shape of the returned data (though an output schema exists). The read-only nature is implied but not stated.

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 minimal and front-loaded with the purpose, followed by a well-formatted args list. Every sentence is functional with no filler.

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

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

For a simple list operation with an output schema and no required parameters, the description covers the essential parameter semantics. It does not discuss return value details, but the output schema presumably handles that. Minor gaps like sort value semantics are inferable from the names.

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 0%, so the description is the sole source of parameter meaning. It clearly enumerates the allowed values for visibility, sort, and explains limit as a maximum. This fully compensates for the schema's lack of 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 'List your GitHub repositories,' which is a specific action and resource. It clearly indicates the tool's purpose but does not explicitly differentiate from siblings like search_repository or repository_summary, though listing vs searching is contextually distinct.

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 provided about when to use this tool over alternatives. The description only lists arguments and offers no context or 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 must disclose behavioral traits, but it only says 'Show', which implies read-only without explicitly stating it. It does not mention permissions, side effects, rate limits, or error conditions, leaving the agent to infer 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?

The description is compact and front-loaded, starting with the core purpose, then listing included statistics, and ending with a clear Args section. Every sentence adds value 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 output schema covers return values, and the description explains the parameter format, making the tool usable. However, it lacks guidance on edge cases (e.g., what if the repo does not exist) and does not clarify how repo resolution works when only 'repo' is provided. Minor gaps prevent a perfect score.

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 provides no description for the 'name' parameter (0% coverage), but the tool description fully compensates by explaining the expected format: 'repo' or 'owner/repo'. This gives the agent the necessary guidance to invoke the tool correctly.

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: 'Show development statistics for a repository' and enumerates specific statistics (language breakdown, commit counts per author, open issues/PRs). This distinguishes it from siblings like repository_summary or dependency_summary, which have different focuses.

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 when development statistics are needed, but it does not provide explicit guidance on when to choose this tool over similar siblings (e.g., repository_summary, dependency_summary). No alternatives or exclusions are mentioned, so usefulness for selection is moderate.

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 provided, so the description carries the full burden. It thoroughly discloses the workflow: detecting project, generating README/.gitignore, initializing git, creating the repo, committing/pushing, and returning URL. This is transparent about side effects.

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 well-structured with a one-sentence overview, bullet-like steps, and an Args section. It's detailed but every sentence serves a 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?

For a multi-step tool with no annotations, the description covers entry conditions, steps, and output (URL). It's sufficiently complete given the output schema exists.

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

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

Schema description coverage is 0%, but the description includes an Args section that explains each parameter's purpose and defaults, significantly adding meaning beyond the schema's bare property definitions.

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 publishes the current working directory as a GitHub repository, with a specific verb and scope. This distinguishes it from sibling tools like publish_project by emphasizing the current working directory.

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

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

The description implies the use case (publishing the current directory) but does not explicitly compare with alternatives such as publish_project. It lacks when-not-to-use guidance, so it's clear context but no 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?

No annotations are provided, so the description carries the full transparency burden. It discloses the side effect (uploading to the Euler repository) and the return value (GitHub URL), but it omits potential failure modes, permission requirements, and whether an existing README will be overwritten.

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

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

The description is compact and front-loaded with the primary action. The Args list is clear and adds value without redundancy. 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?

The description explains the workflow and return value, but it lacks important context such as prerequisites (e.g., existing repository, valid Project Euler problem structure) and error cases (e.g., what happens if problem detection fails). Given no annotations, this leaves the tool less complete for an agent to operate safely.

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?

With 0% schema description coverage, the description must explain both parameters. It does so in the Args section, noting the default for path. However, commit_message is only described as 'optional commit message' without indicating its default or effect, which leaves some ambiguity.

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: 'Publish a Project Euler solution with an auto-generated README.' It enumerates the full pipeline (detect problem, infer metadata, generate README, upload, return URL), which is specific and differentiates it from siblings like upload_euler_solution.

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 clear context for when to use the tool: it operates on the current directory or a specified path, and it auto-generates a README. However, it does not explicitly contrast with alternatives such as upload_euler_solution, nor does it state 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 provided, the description carries the full burden of behavioral disclosure. It transparently lists the full sequence: 'Initializes a git repository if needed, commits all files, creates the remote repository on GitHub and pushes the default branch.' It also explains the defaults for parameters (e.g., repo_name defaults to folder name, branch defaults to 'main'), giving good insight into side effects. It does not mention error scenarios or authentication prerequisites, but core behavior is well covered.

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 front-loaded with a one-sentence summary, followed by a compact step description, and then a clean bullet list of parameters. Every sentence adds information without redundancy. It is well-organized and appropriately sized for the tool's complexity.

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's complexity (6 parameters, multi-step process) and the presence of an output schema, the description is highly complete. It covers parameter semantics, the operational sequence, and defaults. The absence of annotations is offset by the thorough description, making it sufficient for an agent to invoke the tool correctly.

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

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

Schema description coverage is 0%, so the description must fully explain all parameters. It does so explicitly: 'path: absolute path to the local project directory,' 'repo_name: GitHub repository name (defaults to the folder name),' 'private: whether the repository is private,' etc. This adds meaning beyond the schema, which only provides titles and defaults.

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

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

The description clearly states a specific action: 'Publish a local project as a new GitHub repository.' It enumerates the concrete steps (init, commit, create remote, push), which distinguishes it from sibling tools like 'create_repository' (which likely only creates an empty repo) and 'publish_current_project' (which likely operates on the current directory rather than an arbitrary path).

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 clear context for when to use the tool: when publishing a local project as a new GitHub repo. It does not explicitly mention when not to use it or name alternative tools, but the detailed behavior (initializing git, committing all files) implies it is for turning an existing local project into a new remote repository, which is sufficient 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 burden. It discloses the scoring logic (recency, activity, optional interest matching) and parameter behavior, but does not explicitly state whether the operation is read-only, mention side effects, permissions, or limitations. This is useful but not fully transparent.

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 extremely concise: one purpose sentence, one scoring sentence, and a compact parameter list. Every sentence adds value and is front-loaded, with no filler or repetition.

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

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

An output schema is present, so return values are covered externally. The description adds scoring criteria, optional-interest semantics, and parameter definitions, making the tool sufficiently understandable for its moderate 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?

The input schema has no property descriptions (0% coverage), but the description includes a dedicated Args section that defines both parameters: interests as a comma-separated list with an example, and limit as the number of recommendations. This fully compensates for the schema gap.

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 action 'Recommend a project to work on next,' clearly identifying the resource and intent. It distinguishes from sibling repository tools by focusing on next-project selection and scoring by recency, activity, and optional interests.

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?

Establishes a clear usage context: to decide which project to work on next, optionally filtered by interests. It does not explicitly name alternatives or state when not to use this tool, but the context is unambiguous enough for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Return' which implies a read-only operation, but does not mention authentication requirements, error behavior, rate limits, or what constitutes a 'high-level summary'. This lack of detail 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?

The description is highly concise: two short sentences with the primary action front-loaded and parameter documentation efficiently after. Every word earns its place, with no redundancy or filler.

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

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

For a simple one-parameter tool with an existing output schema, the description provides enough information for correct invocation. It doesn't elaborate on the summary's content, but the output schema likely provides that structure. Some nuance about scope is missing, but overall it is adequate.

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 provides only a bare string type with no description (0% coverage), but the description includes an Args section explaining the parameter format ('repo' or 'owner/repo'), adding practical meaning beyond the schema. This compensates well for the missing 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 clearly states the tool's purpose with a specific verb ('Return') and resource ('a high-level summary of a GitHub repository'). It is unambiguous, though it does not explicitly distinguish itself from sibling tools like 'explain_repository' or 'architecture_summary'.

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 provided on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or preferred scenarios, leaving the agent without context for selecting this tool among 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 full responsibility for behavioral disclosure. It only states the search action and parameter semantics, but does not mention auth requirements, rate limits, behavior for private repos, pagination, or error handling. This is a minimal behavioral description beyond the tool name.

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 extremely concise: one clear sentence and a compact Args list. Every line adds value and there is 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?

Given the tool's simplicity, the output schema covers return values, and all parameters are explained. However, without annotations, critical context such as authentication needs or rate limits is missing. The description is largely complete for a basic search tool but lacks some safety/contextual guidance.

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?

With 0% schema description coverage, the description compensates by explaining every parameter: keyword as 'text to search for,' language as an optional filter, owner as a GitHub user/org scoping, and limit as maximum results. These semantics add meaningful value over the bare schema property names.

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

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

The description clearly states 'Search GitHub code for a keyword,' which is a specific verb+resource combination. It distinguishes from siblings like search_repository by targeting 'code' rather than repositories, though it doesn't explicitly mention these alternatives.

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 for searching code snippets via the phrase 'Search GitHub code,' but it provides no explicit guidance on when to use this tool versus alternatives such as search_repository. No exclusions or contextual triggers are mentioned.

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

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

With no annotations provided, the description carries the full burden. It does disclose that the tool searches metadata, READMEs, architecture documentation, and source code, and returns ranked results. However, it does not explain ranking criteria, potential coverage limitations (e.g., archived/private repos), or output structure, though the output schema mitigates the latter.

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

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

The description is compact and front-loaded: the first sentence states purpose, the second adds detail on sources and ranking, and the Args block is a clear, structured parameter list. Every sentence earns its place; no fluff or 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?

For a search tool with an output schema, the description covers the essential aspects: purpose, scope, data sources, ranking, and all parameters. It lacks explicit usage differentiation (addressed in dimension 2) but is otherwise sufficient for correct invocation and interpretation. The absence of annotations is less critical for a read-only search operation.

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 itself has no descriptions (0% coverage), but the description includes an Args block that clearly explains both parameters: 'keyword: the text to search for' and 'limit: maximum number of ranked results to return.' This fully compensates for the schema's lack, adding meaning beyond the type/default information.

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

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

The description clearly states a specific action ('Search') and resource ('your engineering memory across all of your repositories'), with the second sentence enumerating what is searched (metadata, READMEs, architecture docs, source code) and noting ranked results. This differentiates it from siblings like search_code (code-only) and search_repository (likely single-repo) by emphasizing cross-repo scope and ranked output.

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 context: a broad search across all repositories, including documentation and code. However, it provides no explicit guidance on when to use this tool versus sibling tools like search_code or search_repository, and no exclusions or alternative recommendations are mentioned.

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 must carry the full burden of behavioral disclosure. It only says 'Search for repositories by name' and gives param descriptions, but doesn't disclose whether the operation is read-only, whether it hits a rate limit, pagination behavior, or any side effects. This is a clear gap for a tool with zero annotations.

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

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

The description is appropriately sized: a one-line purpose followed by a compact Args list. Every sentence is informative and there is no fluff. Front-loaded with the core action.

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?

This is a simple search tool with only 3 params (1 required) and an output schema is present, so return values need not be explained. The description is sufficient for basic usage, but with no annotations it's slightly bare for a full understanding. It covers the essential semantics without over-explaining.

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 Args section adds meaning beyond the schema: it explains name as 'repository name to search for', owner as 'optional GitHub user/org to scope the search to', and limit as 'maximum number of results'. Since schema coverage is 0%, this description compensates well, though it doesn't detail defaults or edge cases.

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 starts with 'Search for repositories by name', which is a specific verb+resource statement. It clearly distinguishes from sibling tools like list_repositories (which lists all) and search_code (which searches code, not repositories).

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

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

The usage is implied from the purpose: use this when you need to find a repository by name, rather than listing all repositories or searching code. However, there is no explicit statement of when not to use it or what alternatives exist.

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 clearly indicates this is a read-only reporting operation ('List...'), but it does not disclose potential side effects, sorting behavior, or details about output format beyond the parameters. It is adequate but lacks deeper behavioral context.

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 highly concise: one sentence stating the purpose, followed by a structured 'Args' section with two brief explanations. Every word earns its place, and the format is easy to parse.

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 tool with two optional parameters and an existing output schema, the description is complete enough. It covers the purpose and parameter semantics. It could mention ordering or default behavior details, but these are not essential given the tool's simplicity and the presence of an output schema.

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 provides only titles and defaults for the two parameters, with 0% description coverage. The tool description fully compensates by explaining both 'threshold_days' and 'limit' in plain language, making the parameters meaningful and easy to understand.

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: 'List repositories that have not been pushed to recently.' This is a specific verb-resource combination with a clear condition. It is distinct from sibling tools like list_repositories, but it does not explicitly name alternatives, so it earns a 4 rather than 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 the tool (when you need to identify stale repositories), but it provides no explicit guidance on when not to use it or how it compares to alternatives. There are no exclusions or alternative tool references, so usage guidance is only implied.

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

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

With no annotations, the description carries the full transparency burden, but it only mentions the data source (GitHub) and return values. It does not disclose whether this tool mutates any state (despite the 'update_progress' name), whether authentication is required, or whether it fetches live data. This leaves important behavioral traits unspecified.

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 concise sentences, front-loaded with the core verb and resource, and contains no filler or redundant 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?

For a simple no-parameter reporting tool, the description covers the key output and data source. The presence of an output schema fills in return structure details, though prerequisites like GitHub authentication are not mentioned. Overall, it is adequate but not exhaustive.

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

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

The tool has zero parameters, so the schema imposes no burden. The description adds value by explaining what the tool returns, which is enough for a no-parameter tool.

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

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

The description clearly states a specific action: reporting current Project Euler progress from GitHub. It further specifies the exact outputs (solved problems, totals, next unsolved problem), and this distinguishes it from sibling tools like upload_euler_solution and publish_euler_solution.

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

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

The description implies the tool is used when you need your current Project Euler progress, but it offers no explicit guidance on when to prefer it over alternatives like project_statistics or repository_summary. No exclusions or alternative tool references are provided.

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 discloses the storage structure ('problem_<NNN>/<filename>') and the default repository ('project-euler'), which is useful. However, it does not clarify side effects such as whether a commit is created (despite the 'commit_message' parameter), whether the repository is created if missing, if existing files are overwritten, or what the return value is.

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

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

The description is compact and front-loaded. The first sentence states the core action, followed by a helpful storage-location detail, and then a clear parameter list. Every sentence earns its place with no 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 basic usage but lacks completeness in context. It does not explain how this tool differs from the similarly named 'publish_euler_solution', nor does it mention behavior on errors or whether it operates locally versus remote. Given an output schema exists, not explaining return values is acceptable, but the missing usage context and overlap with a sibling reduce completeness.

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

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

Schema description coverage is 0%, so the description's Args section is essential. It provides meaningful explanations for all three parameters: problem_number, file_path (with 'absolute path' constraint), and commit_message (noting it is optional). This goes beyond the bare type information in the schema, though it could add more detail like allowed file extensions.

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 'Upload' and clearly identifies the resource ('a Project Euler solution to your solutions repository'). It also provides the storage path format, but it does not distinguish itself from the sibling tool 'publish_euler_solution', which likely serves a similar or overlapping purpose.

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 explicit guidance on when to use this tool versus alternatives like 'publish_euler_solution'. It implies usage for uploading solutions but provides no when/when-not criteria or mention of alternative tools.

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

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

With no annotations, the description must disclose behavior. It adds the contextual constraint of searching 'your own repositories', but doesn't state read-only nature, permissions, or potential side effects. The behavior is typical for a search tool, so it's minimally adequate.

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

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

The description is extremely concise: one purpose line plus a compact parameter list. Every sentence adds value, and it's front-loaded with the main action.

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's simplicity and the presence of an output schema, the description covers the essential purpose and parameters. It lacks usage guidance and behavioral details, but for a straightforward search operation, it's adequate.

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 description provides full explanations for all three parameters, including an example for language ('python') and the meaning of limit. Since schema coverage is 0%, this fully compensates for missing 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?

Description uses specific verb 'Find' and resource 'keyword in your own repositories', clearly stating the tool's function. The phrase 'your own repositories' differentiates it from broader code search tools, though it doesn't explicitly name alternatives.

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 on when to use this tool versus siblings like search_code or search_repository. The scope is implied by 'your own repositories', but no comparative direction is provided.

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