Return draft tiered responses and contraindications for a Pattern. These are unassessed research guidance, not validated treatment advice. Read the returned evidence and review objects before use.
| Name | Required | Description | Default |
|---|---|---|---|
| severity | No | ||
| dysfunction_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesAdded value: +falseInput schema / properties / dysfunction_id / maxLengthAdded value: +256Input schema / properties / dysfunction_id / minLengthAdded value: +1Input schema / properties / dysfunction_id / patternAdded value: +"\\S"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 clearly discloses that the output is unassessed research guidance, not validated treatment advice, and warns to read returned evidence and review objects. This is valuable behavioral disclosure for a draft/suggestion tool.
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 that pack a lot: what it returns, the caveat about being research guidance, and a clear warning to review before use. It is front-loaded with the purpose and uses 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?
It tells the agent what to expect in the return (draft tiered responses, contraindications, evidence, review objects) and the need for caution. However, it doesn't add needed context for parameter selection or describe how to validate or cross-check with other tool outputs, which is important given no output schema or annotations.
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?
With 0% schema description coverage, the description must explain parameters but only refers to 'a Pattern' without linking to dysfunction_id or severity. It adds no semantic meaning for either parameter, leaving the agent to guess what 'Pattern' refers to or how severity impacts output.
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?
Clearly states the tool 'Return draft tiered responses and contraindications' with a specific resource 'Pattern'. It is distinguishable from sibling tools like score_severity or differential_diagnosis, though it doesn't explicitly mention that the 'Pattern' is referenced by dysfunction_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?
No guidance on when to use this tool versus alternatives. The only usage guidance is 'Read the returned evidence and review objects before use', which is post-call behavior, not a selection criterion.
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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Each tool targets a distinct aspect of the domain: diagnosis, mapping confusions, retrieving entries, elicitation probes, listing axes/dysfunctions/compromised entries, ID resolution, statistics, severity, and interventions. No two tools overlap in purpose; descriptions clearly differentiate them.
Most tools follow verb_noun pattern (get_*, list_*, resolve_id, score_severity, suggest_intervention), but differential_diagnosis and review_stats deviate (noun-like phrases). The inconsistency is minor and doesn't obscure meaning.
11 tools is well within the ideal 3-15 range. Each tool serves a distinct purpose in the diagnostic workflow, and none feel redundant or missing for the stated domain.
The surface covers listing, retrieval, differential diagnosis, probes, severity, interventions, stats, and ID resolution. Minor gaps exist (e.g., no tool to add/update entries or directly compare two dysfunctions), but these are outside the apparent read-only research scope.