get_impact_profile
Return the latest public impact profile for a GitHub handle.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes |
Return the latest public impact profile for a GitHub handle.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide readOnlyHint=true and destructiveHint=false, so the read-only nature is covered externally. The description adds that the profile is 'latest public,' implying freshness and no auth requirement, but it does not mention behavior for unknown handles, empty profiles, or what the returned profile contains. No contradiction with annotations.
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 sentence where every word earns its place: verb, resource, freshness qualifier, access qualifier, and parameter identity. There is no redundancy or 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 single-input, read-only tool the description is mostly sufficient, but with no output schema it leaves the shape of an 'impact profile' undefined and does not address edge cases such as an unknown handle. It would also be more complete with explicit sibling differentiation, given six related tools.
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% and the schema only defines 'handle' as a bare string. The description adds meaningful semantics by identifying it as a 'GitHub handle,' which is the key information needed to invoke the tool correctly. It does not specify format or normalization rules, but with a single parameter the core meaning is supplied.
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 verb (Return), a specific resource (impact profile), and a target (GitHub handle), with 'latest public' adding useful scope. It is clear, though it does not explicitly distinguish itself from siblings such as find_profile or get_impact_history beyond the word 'latest.'
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 guidance on when to use this tool instead of find_profile, get_impact_history, compare_profiles, or verify_badge. The only usage signal is the implied recency of 'latest,' which is not an explicit when-to-use or when-not-to-use statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools target distinct resources or actions: profile data, history, comparison, badge verification, and explanations are clearly separated. The only mild ambiguity is between find_profile and get_impact_profile, since both resolve a GitHub handle to profile-related information.
All nine tools use a consistent verb_noun snake_case pattern (compare_, explain_, find_, get_, verify_). The verbs are specific to their action, making the toolset predictable.
Nine tools is a well-scoped size for a public profile and badge verification service. Each tool covers a distinct user need without redundant or excessive surface area.
The toolset covers the main lifecycle for public Chapa profiles: finding, retrieving, comparing, explaining, verifying, and embedding badges. For a read-only public-info service, there are no obvious dead ends or missing core operations.