Repolode

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

With no annotations, the description must carry the full behavioral burden. It discloses one real trait — results are ordered most-starred first — but nothing about where results come from (presumably GitHub repos), whether output is a list of repos with names/URLs/stars, or any auth/rate-limit constraints. For a search tool with no output schema, this leaves the agent guessing at the return shape.

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 ~20-word sentence with no filler; the input examples and the sort order are both front-loaded. It reads as an efficient fragment rather than a complete spec, which is a gap but not verbosity.

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 is simple (3 params, no nesting, no output schema), and parameters are fully documented in the schema. The remaining meaningful gap is the result shape: an agent cannot tell from the description what fields come back, which matters more because there is no output schema to fall back on.

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 limit, locale and product are all documented in the schema; the baseline is 3. The description adds only an example product value, which slightly reinforces the 'product' parameter but adds nothing about limit or locale 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 names a specific resource (open-source alternatives to a named commercial product) and gives three concrete examples, which clearly distinguishes it from sibling repo/collection search tools. It is a noun phrase rather than a verb-led sentence, so the action ('find') is only implied by the tool name, not stated in the description.

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 examples ('Notion', 'Google Analytics', 'Zapier'), which show the expected input domain, and the sibling set (search_repos, trending, get_repo) is clearly a different kind of lookup. However, there is no explicit statement of when to prefer this tool, nor any exclusion or prerequisite (e.g. whether the product must be commercial, whether a GitHub account is needed).

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 and no output schema, the description carries the full behavioral burden, but it discloses very little. It does not say whether the result includes collection metadata, how pagination or limits behave, error behavior for unknown slugs, or whether locale changes summaries only or also project selection.

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

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

It is a single front-loaded sentence with no wasted words, and it efficiently pairs the operation with the slug source. It is terse to the point that some useful context is omitted, keeping it from a 5.

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 four-parameter getter, the description covers the core action and the slug dependency. But with no output schema and no annotations, the description should say more about what comes back and how the tool behaves on invalid input or with sort/locale options.

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, including defaults and enum values. The description adds only the source of the slug from list_collections, which is useful but marginal beyond the schema.

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

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

The description states a specific verb-resource relation: it returns projects within one topic collection, identified by slug. It distinguishes itself from list_collections by saying the slug comes from that sibling, though it does not explicitly contrast with get_repo or search_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?

It implies the prerequisite flow: first call list_collections to obtain a slug, then call this tool. However, it gives no explicit when-not guidance or comparison against siblings like search_repos or trending.

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

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

No annotations exist, so the description carries the full burden, and it does disclose return content in detail (summary, features, quick start, limitations, license, stars) — valuable given there is no output schema. However, it omits not-found/error behavior, whether the write-up is cached or freshly generated, and any rate or latency expectations for a per-repo fetch.

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

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

A single front-loaded sentence with no filler; the field list is dense but every item doubles as payload disclosure since no output schema exists. Slight cost is that the list crowds out a usage note.

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

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

For a two-parameter read tool with 100% schema coverage but no output schema, the description covers what matters most: the shape of the returned write-up. The remaining gap is routing guidance against siblings and error behavior.

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% and both parameters ('repo' as owner/name or URL, 'locale' with its enum and default) are documented in the schema. The description adds nothing about parameter meaning or format, so the baseline 3 applies.

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

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

States a specific resource and scope: the full write-up of exactly one GitHub project, then enumerates the fields returned. Clear enough to distinguish from a list-oriented tool, but it never names a sibling, so an agent must infer the boundary with search_repos and find_alternatives on its own.

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

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

Usage is only implied by 'one GitHub project' — a single-repo detail lookup as opposed to a multi-result search. There is no explicit 'use this when you already know the repo' statement, no exclusion of search_repos, and no note on what happens if the repo is unknown.

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

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that results include slug and project count, implying a read-only listing, but it does not cover pagination, completeness of results, auth/rate limits, or whether all collections are returned.

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 wasted words, and the examples are useful. It is a noun-phrase fragment rather than a front-loaded verb statement, but it remains easy to scan.

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 a fully described optional locale, the description covers the resource and key returned fields. However, it leaves gaps around result completeness and why an agent would choose it over get_collection or search_repos.

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 single parameter, locale, is fully documented in the schema with its enum and default. The description adds no additional meaning about how locale affects summaries, so the baseline of 3 is appropriate given 100% schema coverage.

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 the resource (Repolode's topic collections), gives concrete examples such as AI agents and MCP servers, and states that each entry includes a slug and project count. It does not explicitly say 'list' or distinguish itself from get_collection, but the resource scope is clear.

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

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

The description gives no when-to-use guidance and does not mention alternatives. It never explains when to use list_collections instead of get_collection, search_repos, trending, or find_alternatives.

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

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

No annotations are provided, so the description carries the full behavioral burden. It helpfully discloses the return fields and implies a read-only search, but it does not explicitly state whether results are paginated, whether authentication is required, or how the search behaves when multiple filters are combined.

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 tightly written sentences with zero waste. It front-loads the core action and follows with the return shape.

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

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

No output schema exists, so the description appropriately lists the fields returned. Combined with the fully documented schema, an agent has enough to call the tool correctly, though it does not address pagination or rate-limit behavior.

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. The description reinforces that search can be scoped by keyword, category, or programming language, but adds no format or syntax detail beyond the schema.

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

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

The description states a specific verb and resource: search Repolode's curated open-source projects. It distinguishes the tool from the single-repo sibling get_repo by implying broad discovery, but it does not explicitly clarify its relationship to trending or find_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?

Usage is implied by 'search ... by keyword, category or programming language', which indicates broad discovery. However, the description gives no explicit when-to-use or when-not-to-use guidance relative to siblings like trending or find_alternatives.

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

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

With no annotations, the description carries the full burden and does usefully disclose the ranking criterion and 7-day window — genuine behavioral context. However it says nothing about result ordering guarantees, data freshness/caching, or what a returned 'project' contains.

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

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

A single front-loaded sentence that defines resource, metric, window, and optional filter with zero 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 read-only, zero-required-parameter listing tool this covers what is needed to call it correctly. With no output schema, a brief note on the shape of each returned project would have closed the remaining gap.

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%, including enum values and the limit maximum, so the schema already documents everything. The description only echoes the category filter and adds no semantics for limit or locale beyond the schema.

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

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

States a specific resource (projects/repos), a specific ranking metric (stars gained), and a precise time window (last 7 days), optionally scoped to one category. An agent can tell this apart from get_repo or search_repos, though no sibling is named 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 phrase 'optionally within one category' implies the main usage pattern but gives no explicit when-to-use versus search_repos or find_alternatives, and no exclusion conditions. Guidance is inferable rather than stated.

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