AskHound

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 only states the transformation and output categories; it does not disclose authentication needs, rate limits, determinism, execution side effects, or any return format details.

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

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

The description is a single front-loaded sentence with no filler or repetition. It is appropriately sized for a high-level purpose statement, though the lack of supporting details keeps it from being maximally useful.

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 tool with four undocumented parameters, no annotations, and no output schema, the description is incomplete. It gives the broad purpose and output categories but omits parameter semantics, usage context, and behavioral details needed to invoke it confidently.

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% for four parameters, so the description must compensate. Instead, it does not explain the meaning, format, or role of jobs, product, category, or competitors, leaving all parameter semantics undocumented.

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: turning a product description into buying-intent search phrases. It also enumerates output categories, making the tool's purpose clear. However, it does not distinguish this tool from the sibling run_intent_pack, which may also relate to intent queries.

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

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

There is no explicit guidance on when to use this tool versus alternatives such as run_intent_pack, nor any prerequisites or exclusions. The description implies a use case but leaves routing decisions entirely to the agent.

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 well: it discloses the source coverage, the return fields (url, title, snippet, date, source, attribution), and a key safety boundary ('Never auto-post replies'), implying a read-only search. It doesn't mention rate limits, auth requirements, or result pagination, which keeps it below 5.

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-loads purpose in the first clause, then layers routing and return info efficiently. The embedded npx install string is long but functional and necessary. Overall dense but each 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?

For a read-only discovery tool with no output schema, the description lists the returned fields and explains multi-source routing, which is what an agent needs to interpret results. The remaining gap is parameter-level detail that the sparse schema does not supply.

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 only 33% (only query and context are documented) and the description adds no parameter-level meaning — days, limit, exclude, and sources are never explained. The source routing sentence hints at the 'sources' enum but does not describe how to use the parameter, so the description fails to compensate for the coverage 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?

States a specific verb ('Find') plus a tightly scoped resource ('recent public posts where people ask for a tool, an alternative, or help with a job'), including the qualifying intent of the posts. This is clearly distinguishable from the sibling tools (query building, reply policy, intent packs), so an agent knows exactly what this retrieves without opening the schema.

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

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

The description gives explicit downstream context ('so you can decide whether an honest, disclosed reply would help them') and a concrete routing rule: remote covers Stack Exchange/Bluesky, while Hacker News + GitHub require the local MCP invocation. It stops short of naming a sibling as an alternative or stating when NOT to call it, but the when-to-use signal 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?

No annotations exist, so the description carries the full burden. It discloses the content's nature (rules users agreed to) and a usage precondition, but says nothing about what is returned (full text vs. summary), whether it is static, or any side-effect/safety profile. Modest context, significant remaining 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 short sentences, front-loaded with the resource identity followed by the actionable instruction. No wasted words.

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

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

For a zero-parameter tool with no output schema, the description should clarify what the agent receives back, and it does not. It is adequate for identification and timing but leaves the return contract undefined.

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?

Zero parameters, which earns the baseline 4. No parameter semantics are needed and none are missing.

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?

Names a specific resource – the 'honest-reply rules AskHound users agree to' – which clearly distinguishes it from siblings like build_intent_queries and find_conversations. However, it never states the action the tool performs (retrieves/returns the policy text); the verb is only implied by the imperative 'Read'.

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?

'Read before drafting any reply' gives a clear precondition for invocation. It stops short of naming alternatives or when-not-to-use cases, but for a single-purpose reference tool the timing guidance is unambiguous.

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 full disclosure duty, and it does contribute real behavioral facts: results are merged, deduplicated, and ordered newest first. It is silent on everything else an agent wants for a 6-parameter aggregation call — rate limits, permissions, how the two upstream queries are scoped, and what the response actually 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?

One compact sentence, correctly front-loaded with the composed action before the merge/dedup/order qualifiers, and 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 an aggregating tool with six undocumented parameters, no annotations, and no output schema, the definition is far too thin: it never defines what qualifies as a 'phrase', how the parameter set drives the two underlying queries, or what a merged/deduplicated result looks like. Only the ordering and dedup semantics are covered.

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% across six parameters (days, jobs, context, product, category, competitors), and the description explains none of them — its only temporal hint, 'newest first', is about output ordering, not the 'days' window. Nothing compensates for the undocumented schema, so an agent cannot tell which inputs scope the intent queries versus the conversation search.

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?

It states a concrete composition: run build_intent_queries plus find_conversations, then merge, deduplicate and sort by recency, and it names the two sibling tools it wraps, which separates it from build_intent_queries and find_conversations. However the phrase 'for every phrase' never maps onto any actual input field, so the scope is partly ambiguous.

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?

By describing itself as the union of two named sibling tools, it implies usage: reach for this when you want both result sets combined in one pass instead of calling each separately. There is no explicit when-not guidance or statement of what you lose (e.g., per-tool filtering) by choosing this over the siblings.

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