RepoAlerts

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds real value beyond that: the data source (GitHub repos RepoAlerts tracks), that star counts and growth are real, and the ranking rule that self-declared replacements surface first. It stops short of describing result volume or failure 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?

Three sentences, front-loaded with the core purpose before the optional constraint and ranking behavior. Nearly every clause earns its place, with only minor overlap between the required input mention and the schema.

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

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

An output schema exists, so return-value explanation is not needed, and the description covers the data source, ranking, and optional filters well enough to call the tool correctly. The one gap is the absence of any routing guidance against sibling tools, which leaves the agent to infer tool selection.

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

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

Schema description coverage is 100%, so the schema already documents every parameter including the enum values and defaults. The description reinforces the 'to' and optional platform/constraint semantics with examples but adds no syntax or format detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 ('Finding open-source alternatives to an app, product or service') and grounds it with concrete examples ("Photoshop", "Notion", "Heroku", "Postman"). The scope is unambiguous and clearly distinct from get_repo, search_repos, and trending_repos, which retrieve repos rather than alternatives to a given product.

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

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

Usage is implied by the phrasing: use it when you want alternatives to a named product, optionally constrained by platform. However, it never states when to prefer this over sibling tools like search_repos, nor what inputs make it fail (e.g. unknown app). The guidance is present but inferential rather than explicit.

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

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: what happens on a miss (it says so) and why a repo may be absent (unknown or excluded for fake stars). Auth, rate limits, and freshness/caching are unaddressed, keeping it out of the top band.

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

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

Three sentences, each doing distinct work: payload contents, usage context, and miss behavior. The field enumeration is long but front-loads the value; nothing is padded, though the list could be tightened.

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?

A single-repo lookup with an output schema, full param coverage, and clear annotations is well covered; the description sensibly adds the negative-case behavior the schema cannot express. Enumerating return fields is mildly redundant given the output schema, but nothing an agent needs to call it correctly is missing.

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

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

Schema description coverage is 100%, so the schema already documents 'owner/name' or URL and the locale enum with its Spanish-use guidance. The description's '(owner/name or URL)' and return-field list add no parameter semantics beyond the schema, making the baseline 3 correct.

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 — retrieve everything RepoAlerts knows about a single GitHub repository — and enumerates the data returned (stars, star curve, licence, last push, replacements, HN stories, similar repos). The single-repo scope implicitly separates it from the search/discovery siblings, but no sibling is named explicitly, so it falls short of full sibling differentiation.

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

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

'Use it to check a repo before recommending or installing it' gives a clear use context. However, it offers no when-not guidance and never points at find_alternatives, search_repos, or trending_repos as the alternative for discovery-style queries.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and non-destructive, so the safety profile is covered. The description adds non-obvious provenance context — that the directory excludes repos with bought or farmed stars — which meaningfully affects how much the agent should trust the results.

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

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

Front-loaded with the core purpose and the anti-pattern guidance before enumerating return fields, and every clause carries information. The trailing list of returned fields is somewhat verbose given an output schema exists, but it is not wasteful enough to penalize more heavily.

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 8 parameters (3 enums), full schema coverage and an output schema present, the description covers purpose, usage trigger, data provenance and result scope adequately. The enumerated return fields partially duplicate the output schema, but nothing an agent needs to invoke the tool correctly is missing.

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

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

Schema description coverage is 100% and every parameter, including enums and defaults, is documented in the schema itself. The description only echoes one example query, adding no syntax, format, or interaction detail beyond what the schema already provides, so the baseline of 3 applies.

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

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

States a specific verb (find) and resource (open-source GitHub repositories) with a clear qualifier ('real, actively growing') and the underlying data source (semantic search over the RepoAlerts directory). It is clearly distinguishable from siblings like get_repo or trending_repos.

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

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

Explicitly says to use it instead of recalling package or repo names from memory whenever the user asks for a tool, library, app, framework or MCP server — a clear when-to-use condition and an anti-pattern to avoid. It does not, however, name sibling alternatives such as find_alternatives, which would make the routing guidance complete.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds genuine behavioral context beyond them: spam/star-farm filtering and the star-gain basis of the ranking. It does not cover pagination or rate limits, which is the only 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?

Two sentences, front-loaded with the core behavior, then filters, then the usage trigger. No filler; every clause carries 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?

With an output schema present, return values need not be explained, and the description fully covers purpose, filters, and the star-farm quality guarantee. The only shortfall is that it omits the 'year' period and the 'locale' option, both of which live entirely in the 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?

Schema description coverage is 100%, so the schema already documents every parameter including enum meanings. The description restates the topic and kind filters and lists three of the four period values (omitting 'year'), so it adds marginal value rather than new semantics. Baseline 3 applies.

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

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

The description names a specific resource (GitHub repos) and a specific measure (most stars gained in a window), plus a distinguishing quality trait (star farms filtered out). It separates this from siblings search_repos and find_alternatives, which are query-driven rather than trend-driven.

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

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

It gives an explicit trigger: 'Use it when the user asks what's new, hot, trending or taking off in open source.' That is clear context for selection. It does not name when to prefer a sibling (e.g. search_repos for keyword queries), so it stops short of full routing guidance.

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