Indie Alternatives

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that this is a lookup by id from a prior search, but says nothing about behavior on unknown ids or what the returned 'full description' includes.

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 sentence that front-loads the action and the key dependency (id from search_tools). No wasted wording.

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 one-parameter read-only lookup with full schema coverage and no output schema, the description covers the essential dependency chain. Minor gap: no mention of error behavior for invalid ids or what fields the full description returns.

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 the schema already documents the id parameter as returned by search_tools. The description reinforces that provenance, which is the one semantic detail that matters, but adds no format or constraint details 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 verb (get full description) and resource (product by id), and explicitly links it to the sibling search_tools as the source of the id. Differentiation from siblings is implied by the search-then-fetch pairing, though it is not spelled out.

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 by tying the id to search_tools, which gives a workflow hint (search first, then fetch details). It does not state when not to use it or what happens with an id that doesn't 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?

The description goes far beyond basic annotations by detailing critical privacy behaviors, such as ensuring anonymity, the exclusion of PII like names and IP addresses, and the redaction policy.

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?

While informative, the description is slightly dense, but every sentence provides unique, high-value information that isn't in the schema or annotations.

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 sensitive nature of recording user needs, the definition is exceptionally complete, covering purpose, usage rules, and critical data handling protocols.

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 reinforces the nature of the required inputs, explicitly stating that data sent must be generic and stripped of personal identifiers, providing essential guardrails for parameter population.

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 tool's purpose is extremely clear: to record a user's unmet need so that developers can discover what to build. This distinguishes it well from sibling tools like search_tools or get_tool_details which retrieve information.

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 provides a perfect 'when to use' scenario: call this tool when no other tool in the catalog satisfies the user's current request.

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 cover the read-only and closed-world safety profile, so the description's added value is the disclosure that results come from an indie-product catalog and that a `matched=false` signal exists as the empty-result contract. With no output schema, surfacing that boolean is genuinely useful. It stops short of describing ranking, ordering, or what fields each result carries.

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 short sentences, front-loaded with the invocation trigger, then the mechanism, then the failure path. Every sentence carries distinct operational information 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 five-parameter search tool with a fully documented schema and no output schema, the description covers trigger, mechanism, and the key empty-result signal. What is missing is only secondary: result shape, ordering, and whether the optional filters narrow or merely rank.

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 query, limit, pricing, category, and platform are all documented in the schema itself. The description adds no extra semantics such as how matching is done, whether pricing/category/platform are hard filters or soft boosts, or what happens with an overly narrow category. 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 ('Matches the need against a catalog of indie-made products') and scopes it to indie products, which is a meaningful differentiator. It also names the routing target when nothing is found (log_unmet_need), so the agent can place this tool relative to siblings without opening schemas.

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 trigger conditions ('when the user asks whether there is a tool for X, or for an alternative to a product') and an explicit fallback path when matched=false. Both when-to-use and what-to-do-next are stated, leaving nothing to inference.

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