Retrieve a deep diagnostic dossier for a learner candidate by ID, email, or name. Returns statutory DLTC readiness, triple-hurdle breakdown (Rules, Signs, Controls), test history trajectory, top 5 recurring mistakes, and coaching recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| No | Candidate email address | ||
| query | No | Partial search string (name, email, or ID) | |
| candidate_id | No | Candidate ID (e.g., 'cand_1790407702410_90469b00') |
Changes observed during successful MCP inspections.
Input schema / properties / candidate_id / descriptionPrevious value: -"Candidate ID (e.g., 'cand_1790407702410_90469b00') [Optional: omit to use server default filter]."New value: +"Candidate ID (e.g., 'cand_1790407702410_90469b00')"Input schema / properties / email / descriptionPrevious value: -"Candidate email address [Optional: omit to use server default filter]."New value: +"Candidate email address"Input schema / properties / query / descriptionPrevious value: -"Partial search string (name, email, or ID) [Optional: omit to use server default filter]."New value: +"Partial search string (name, email, or ID)"Input schema / properties / candidate_id / descriptionPrevious value: -"Candidate ID (e.g., 'cand_1790407702410_90469b00')"New value: +"Candidate ID (e.g., 'cand_1790407702410_90469b00') [Optional: omit to use server default filter]."Input schema / properties / email / descriptionPrevious value: -"Candidate email address"New value: +"Candidate email address [Optional: omit to use server default filter]."Input schema / properties / query / descriptionPrevious value: -"Partial search string (name, email, or ID)"New value: +"Partial search string (name, email, or ID) [Optional: omit to use server default filter]."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 does disclose the payload shape (readiness, hurdle breakdown, trajectory, top 5 mistakes, coaching), which is valuable since there is no output schema, but it omits key behavioral facts: whether the call is read-only, what happens if zero or multiple candidates match (0 required params), and whether ambiguous name lookups error or return a list.
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 sentences, no filler, with the purpose front-loaded ahead of the return-value inventory. The second sentence is a dense but useful enumeration rather than padding.
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?
Because there is no output schema, the description rightly summarizes return contents, which covers the biggest gap. However, with no annotations and zero required parameters on a multi-key lookup, the definition is silent on resolution/ambiguity behavior and on safety profile, leaving a real gap for an agent calling it blind.
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 the schema already documents all three parameters; baseline 3 applies. The description restates the lookup keys ('by ID, email, or name') and so adds only marginal mapping value, and does not explain precedence or what happens when 'query' matches multiple candidates.
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 ('Retrieve') and resource ('deep diagnostic dossier for a learner candidate') and enumerates the lookup keys. The adjective 'deep diagnostic' implicitly separates it from the sibling get_candidate_summary, but the description never names that sibling to make the distinction explicit.
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 is only implied: 'deep diagnostic' hints this is the heavier alternative to get_candidate_summary, but there is no explicit when-to-use / when-not-to-use statement or named alternative. An agent must infer the routing rule from the sibling name alone.
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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