GrantIQ

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

With no annotations provided, the description carries the full burden and does well by disclosing partial-update semantics, server-side taxonomy filtering for beneficiary/mission tags, and the return behavior of saved=true. It also hints at the interactive nature ('via chat') but omits details like error handling or authentication requirements.

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 four short, information-dense sentences. It front-loads the purpose, then delivers critical semantics, a filtering detail, and a clear next-step instruction. No wasted words; every 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 complex nested object with 15 fields and no output schema, the description covers the core purpose, update semantics, data validation, and post-condition. It lacks details on failure modes or authentication, but given the tool's interactive chat nature, this 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 has zero descriptions (0% coverage), so the description must compensate. It adds valuable overall semantics: null/missing fields leave existing values untouched, and beneficiary/mission tags are filtered to canonical taxonomies. However, it does not explain individual parameters beyond their self-explanatory names in the schema, so it provides only partial compensation 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?

The description clearly states the tool's function: 'fills in the user's matching profile field-by-field via chat.' This distinguishes it from sibling tools like find_opportunities (searching) and should_apply (decision-making), making the purpose unmistakable.

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 clearly indicates the tool is for profile completion in a chat context and prescribes the next step: 'After this returns saved=true, call find_opportunities to see matches.' However, it does not explicitly state when not to use it or name alternative tools for similar tasks, so it falls short of a 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 carries full burden. It discloses detailed response contents (summary, funds, constraints, mechanics, eligibility, citations) and caching behavior with sub-50ms performance. It does not explicitly state read-only behavior, but this is a minor 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?

The description is concise, consisting of two sentences. It is front-loaded with the core purpose ('plain-English unpack of a single grant') and every clause adds value, including response contents and caching performance.

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 no output schema, the description thoroughly enumerates the return categories, giving an agent a clear picture of what to expect. It also covers caching behavior. Minor omission of error handling is acceptable given the tool's simplicity.

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 3 applies. The description does not add parameter-specific details beyond the schema; the schema already describes grant_id as a UUID from prior searches. The description's mention of 'single grant' aligns with the parameter but offers no extra semantic value.

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 it explains a single grant in plain English, using a specific verb ('unpack') and resource ('single grant'). This distinguishes it from sibling tools like search and find_opportunities, which are for discovery rather than detailed explanation.

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 for a single grant and the schema's parameter description notes the ID comes from prior search calls, but the description itself lacks explicit 'use this when' guidance or comparisons with alternatives. It is clear enough but could be more 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?

With no annotations, the description carries the full burden of disclosing behavior. It reveals a critical privacy/security feature: the 'not found' response is identical for unknown grants and grants not open/visible, preventing information leakage. This is valuable behavioral context beyond what annotations would typically convey. It does not mention authentication or rate limits, but for a simple fetch operation the core behavior is well 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 two sentences with no wasted words. The first sentence states the core action and resource; the second adds essential usage constraint and edge-case behavior. Every clause contributes value, and the structure is front-loaded with purpose.

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 (one parameter, no output schema, no annotations), the description is remarkably complete. It covers the action, the source of the id, and the important not-found behavior for privacy. The only minor gap is not specifying what fields constitute a 'full record', but that may be assumed to be the grant object from search context.

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 covers the id parameter fully (UUID from prior search), so the baseline is 3. The main description repeats the prior-search requirement but adds no new semantic meaning beyond the schema. Thus, the description does not enhance parameter understanding further.

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 'return' and the resource 'full record for a single grant by id', which precisely defines the tool's function. It also distinguishes from siblings like 'search' (which returns multiple results) by emphasizing the single-record scope and the requirement for a prior search id.

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 explicitly says the id must come from a prior 'search' call, which guides when to use this tool. It also explains the 'not found' behavior for open/visible grants, providing context for interpreting results. However, it does not explicitly mention alternative tools for other scenarios, so it lacks full exclusion 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 is the sole source for behavioral disclosure. It reveals that the tool runs the profile through a matching engine and requires a complete profile, but it does not discuss side effects, error behavior, output shape, or any potential cost/limitation. This is adequate but 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?

The description is concise (two sentences) and front-loaded with the main purpose. However, it includes a redundant 'GrantIQ find_opportunities:' prefix and an unnecessary internal service name ('canonical StagedMatchingService'), which are minor distractions.

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 tool with one parameter, the description offers the essential purpose and a key precondition. However, without an output schema, it leaves the result structure unspecified, and there is no mention of what happens if the profile is incomplete. It is minimally complete but not comprehensive.

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 'limit' is fully described in the schema (100% coverage), so the description need not add more. The baseline of 3 applies because the schema already documents the parameter meaning.

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 runs the user's profile through an AI matching engine to find top grants, using a specific verb-resource pair. This distinguishes it from sibling tools such as search (likely keyword-based) and explain_opportunity (explains a specific grant).

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 includes an explicit prerequisite ('Requires a complete profile'), giving clear context for when the tool is appropriate. However, it does not explicitly name alternative tools or exclusions, so it lacks full when-to-use/not-use 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 provided, the description carries the full burden of behavioral disclosure. It discloses a key filtering behavior (only currently-open, AI-enriched grants; closed/suspended/unpublishable never returned) and indicates ranked ordering. It also clearly states the return format (id, title, funder, deadline, amounts). It doesn't mention rate limits or error handling, but for a read-only search tool this is a reasonably complete behavioral picture.

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: purpose, return-linkage, and filtering behavior. It is front-loaded with the main action and does not waste words. The inclusion of 'GrantIQ search:' is slightly redundant but acceptable. Overall, it is 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 has 2 parameters, no output schema, and no annotations, but the description compensates by explicitly listing the returned fields and the filtering behavior. It provides enough context for an agent to use the tool effectively: what it returns, how to use it with `fetch`, and what is excluded. Minor gaps like pagination details or ranking rationale are not critical for basic usage.

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 input schema provides robust descriptions for both parameters (query matches title/summary/description; limit has range and default). The description adds little beyond what the schema already states, leaving the baseline at 3. It does mention the ranked list indirectly, but parameter semantics are fully covered by 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 clearly states the tool's function: finding UK & EU grants via free-text query. It specifies the resource (grants), the action (search/find), and the scope (UK & EU, currently-open). It also distinguishes itself from the sibling `fetch` tool by noting that it returns summaries for later full-detail retrieval, making its role in the workflow unambiguous.

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 guidance is implied through the free-text query description and the explicit advice to pass returned references to the `fetch` tool for full detail. While it doesn't mention alternative tools like `find_opportunities` or state when not to use search, the context is sufficiently clear for an agent to select this when a free-text search is needed and a fetch is desired afterward.

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. It adds meaningful behavioral context by describing the decision output, the 'unknown' competition-risk case when funder data is absent, and the profile requirement. It does not disclose side effects, rate limits, or error modes, but for a read/evaluate tool this is a moderate 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?

The description is two sentences: the first defines the tool and lists all outputs, the second states the prerequisite. It is front-loaded, avoids repetition, and every clause contributes to the agent's understanding.

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 moderate complexity and the absence of an output schema, the description thoroughly covers the purpose, return values, an edge case (unknown competition risk), and the prerequisite. Minor gaps remain around error conditions or confidence computation, but these are not essential for tool selection and invocation.

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 explains grant_id as a UUID typically returned from prior search calls. The description adds a related prerequisite about the caller's profile, but it does not significantly enhance the parameter understanding beyond what the schema provides, meeting the baseline.

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: 'opinionated apply / don't-apply decision for a specific grant.' It explicitly lists the returned verdict, confidence, blockers, effort estimate, competition-risk label, and evidence. This verb+resource+scope wording distinguishes it from sibling tools like search or explain_opportunity.

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 states a prerequisite ('Requires the caller's profile to be set via a prior find_opportunities call or web sign-up') which implies usage after profile setup, but it does not explicitly say when to use this tool instead of alternatives or mention exclusion criteria. The context is clear but not comparative.

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