Qumge Skills

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

With no annotations, the description carries the full burden. It discloses that the tool returns SKILL.md files and instructs the agent to write them to disk, which is a helpful behavioral guideline. However, it does not mention whether the fetch is read-only, how errors are handled, or the exact response format, leaving some transparency gaps.

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 action, and every clause serves a purpose—fetching, writing, and installing. There is zero redundancy or filler, making it highly concise and well-structured.

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

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

The tool is simple (one required parameter, no output schema), and the description covers the main flow: fetch, write, install. It gives the installation path and mentions the slug source, which is sufficient for the tool's complexity. It could be more explicit about the return structure, but for a bulk fetch it is adequately 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 already documents the slug parameter with an example ('bundle:competitor-research') at 100% coverage. The description adds slight context by pointing to list_bundles as the source of the slug, but does not add substantial meaning beyond the schema, so a 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 opens with 'Fetch every SKILL.md in one bundle, in a single call', which uses a specific verb (fetch) and resource (bundle of SKILL.md files). It clearly distinguishes from siblings like get_skill (single skill) and list_bundles (lists bundles) by framing this as a bulk fetch operation.

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 a clear usage flow: get the slug from list_bundles, then call this to fetch and install all skills, noting 'no other step is needed'. It implies when to use (when you want the whole bundle) but does not explicitly contrast with alternatives like get_skill for individual skills, so it lacks an explicit exclusion.

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 transparently explains the output (full SKILL.md content), the installation side effect (writing to .claude/skills/<name>/SKILL.md), and that no further steps are required. It does not cover error conditions or authentication, but the behavior is straightforward and well-described.

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 that are front-loaded with the purpose, then followed by actionable installation guidance. Every phrase earns its place: the source of the slug, the destination for writing, and the note that no other step is needed. 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?

For a single-parameter tool with no output schema, the description is complete. It explains the input source, the output content, and the exact post-processing step required, making the agent aware of the full workflow. The sibling tools are contextually relevant, and this description fills all functional 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?

The schema description already provides full coverage (100%) for the slug parameter, including an example and reference to search_skills. The tool description reinforces the same information ('slug returned from search_skills') without adding new semantic detail beyond what the schema already states.

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 verb ('Fetch') and resource ('full SKILL.md content of one skill'), and distinguishes it from sibling tools by referencing the slug returned from search_skills. This makes it obvious how get_skill differs from list_bundles, search_skills, etc.

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 clear context: use the slug from search_skills, and after fetching, write the file to the specified path to install. It implies the workflow (search → get → install) and provides a 'no other step is needed' assurance. However, it does not explicitly mention when not to use this tool or name 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 carries the burden. It clearly indicates a read-only 'List' action and implies that installation is handled by get_bundle, not this tool. It could further disclose output details, but the behavior is sufficiently 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?

Two concise sentences, front-loaded with the core action. The definition and usage guidance are packed efficiently without unnecessary 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?

For a 0-parameter list tool, the description is largely complete: it defines bundles, explains when to use the tool, and directs to the next step. It doesn't specify the exact fields returned, but the lack of an output schema and low complexity make this acceptable.

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, and the schema coverage is 100% (trivially). The description adds conceptual context about bundles, which is useful but not needed for parameter understanding. Baseline 4 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?

Uses a specific verb+resource ('List Qumge's skill bundles'), defines what a bundle is, and clearly distinguishes from siblings like get_bundle which installs bundles. The example ('see what competitors are posting') anchors the 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?

Explicitly states when to use this tool: when the user describes a goal rather than naming a tool. It also tells the agent to follow up with get_bundle to install, providing clear next-step 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?

With no annotations, the description carries the burden of behavioral disclosure. It clearly indicates this is a read-only listing operation (via 'List') and discloses the return shape (categories and counts). It does not mention potential limitations like sorting or pagination, but for a simple list tool this is 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 two short, front-loaded sentences. The first sentence states the core function, and the second adds usage context. Every word earns its place, with no redundant or vague phrasing.

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 (no parameters, no output schema), the description is fully sufficient. It explains what the tool returns (categories and counts) and provides usage context. There are no hidden complexities or dependencies that need further explanation.

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 baseline is 4. The description adds no parameter information because none exists; the schema is empty and the description does not need to compensate for any parameter documentation gaps.

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 ('List') and resource ('skill categories'), and explicitly mentions the return content ('how many skills are in each'). This distinguishes it from sibling tools like list_bundles and search_skills, which focus on different resources or actions.

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 when-to-use guidance: 'Useful when the user is browsing rather than looking for something specific.' This implies a contrast with search_skills, but does not explicitly name alternatives or state when not to use the tool, stopping short of a full 5.

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 behavioral disclosure burden. It does well by revealing that all models are reachable with the same Qumge key (no per-vendor signup), only tool-calling models are listed, and ordering is 'best first.' These are non-obvious behaviors beyond a generic list. It does not mention pagination or error cases, but the key behavioral traits are 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 three sentences, each earning its place: the first states the core function and ordering, the second clarifies authentication, and the third sets an important constraint. It is front-loaded with the action and resource, with 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?

Given the tool's simplicity and no output schema, the description adequately covers what an agent needs: what models are listed, how they are ordered, the authentication benefit, and the tool-calling filter. It does not specify the exact return fields or error behavior, but for a model-listing tool, the information provided 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 already fully describes both parameters (limit and query) with clear descriptions, so schema coverage is 100%. The description adds minimal extra parameter-related context—it does not elaborate on how the filter works beyond what the schema says. Per baseline, a score of 3 is appropriate when the schema carries the explanatory load.

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 the models this gateway can route to, best first.' It specifies the resource (models), the action (list), and adds a helpful qualifier ('best first') plus a scope restriction ('Only tool-calling models are listed'). This distinguishes it from sibling tools that deal with bundles, skills, or categories.

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: whenever an agent needs to see available models that can be routed to, notably with the same Qumge key. It also gives an exclusion hint: models that are not tool-calling are not listed, so if you need those, this tool is not sufficient. However, it does not explicitly mention alternative tools, though none of the siblings are model-related.

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, description carries full burden. It discloses ranking method (LLM read each one), return contents (one-line summary, slug), and browse behavior when query omitted. Could mention pagination details but schema covers offset/limit; still well beyond 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?

Two sentences, front-loaded with action and resource, includes examples and return info. Every word earns its place, 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?

No output schema, so description must explain return values—it does (one-line summary, slug, ranked best few). Combined with schema details, the description sufficiently covers purpose, usage, behavior, and integration with get_skill.

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 baseline is 3. Description adds minimal parameter semantics beyond schema, mostly repeating that query is in user's words and that omitting it browses top-ranked. No significant added value for limit/offset/category.

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 states an explicit verb (Search), resource (Qumge's curated catalog of agent skills / SKILL.md files), and purpose (by what the user wants to accomplish). It distinguishes from siblings by noting result includes the slug to pass to get_skill, and category param references list_categories.

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?

Gives explicit when-to-use: 'Use this whenever the user asks for a skill, tool, or capability' with examples. It also provides an alternative/next-step by mentioning the slug is for get_skill, and references list_categories for category browsing.

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