Report an explicitly shared success, failure, applicability result, or unresolved gap.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| outcome | Yes | ||
| idempotency_key | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds the qualifier 'explicitly shared' to scope the action, which is useful context. However, it does not disclose what happens to the report (e.g., whether it creates a persistent record) beyond the annotation-provided safety profile.
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 of 13 words. Every word contributes meaning with no redundancy or padding. It is exemplary in conciseness.
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?
Despite having an output schema and annotations, this is a mutation tool with 3 parameters including a nested object and low schema coverage. The description is too terse to give complete context on when and how to invoke it correctly. It omits key behavioral details like idempotency semantics, required fields, and the purpose of 'slug' or 'idempotency_key'.
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%, so the description must compensate. It mentions the result categories (success, failure, etc.) which aligns with the 'result' field, but it does not explain 'slug', 'idempotency_key', or the nested 'outcome' object structure. The agent would have to rely on the schema alone, which lacks top-level descriptions.
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 reports an explicitly shared success, failure, applicability result, or unresolved gap. It uses a specific verb ('report') and identifies the resource and scope ('knowledge outcome'), distinguishing it from sibling tools like submit_experience or verify_experience.
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?
No guidance is provided on when to use this tool versus alternatives such as submit_experience or get_knowledge. The description only states what it does without clarifying the decision context, leaving the agent without explicit exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action: problem lifecycle, knowledge reading/search/context, candidate submission/review, and experience verification. Even similar tools like get_knowledge, search_knowledge, and retrieve_context are clearly differentiated by their descriptions.
All tool names follow a consistent snake_case verb_noun pattern with no mixed conventions or vague verbs. Names accurately reflect their actions and objects, making the set predictable and easy to navigate.
At 16 tools, the count is slightly above the typical 3-15 range but still reasonable given the multi-faceted domain (problems, knowledge, candidates, experiences). Each tool appears to have a specific purpose, though a few could potentially be consolidated.
Core workflows are covered: create/claim/manage problems, submit/review candidates, publish/retrieve knowledge, and verify experiences. Minor gaps exist such as no explicit close/cancel operation for problems, but agents can work around these with existing tools.