Filtered list of dysfunctions. Filter by axis, self_report reliability, confidence, or category. Every entry carries its reliability and review signals.
| Name | Required | Description | Default |
|---|---|---|---|
| axis | No | Filter by axis number (2-10). Canonical entries only unless category is also set; axis=10 with category='hybrid' returns the 10.4-10.15 sub-category. | |
| category | No | ||
| confidence | No | ||
| self_report_reliability | No | Filter by the exact self_report reliability value. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesAdded value: +falseInput schema / properties / axis / descriptionPrevious value: -"Filter by axis number (2-10; canonical only)"New value: +"Filter by axis number (2-10). Canonical entries only unless category is also set; axis=10 with category='hybrid' returns the 10.4-10.15 sub-category."Input schema / properties / axis / maximumAdded value: +10Input schema / properties / axis / minimumAdded value: +2Input schema / properties / categoryAdded value: +{
+ "enum": [
+ "canonical",
+ "hybrid"
+ ],
+ "type": "string"
+}Input schema / properties / self_report_reliability / descriptionPrevious value: -"Filter by self_report value: reliable | partial | scaffolded-only | unreliable | compromised-motivational | compromised-structural | compromised"New value: +"Filter by the exact self_report reliability value."Input schema / properties / self_report_reliability / enumAdded value: +[
+ "partial",
+ "unreliable",
+ "compromised-motivational",
+ "compromised-structural"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only discloses that each entry includes reliability and review signals, but does not explain default behavior when no filters are applied, how multiple filters combine (AND/OR), sorting, pagination, or any limitations.
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 short sentences with no filler. It front-loads the core purpose and filters, and each sentence adds distinct value (function, filters, content guarantee).
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 and no annotations, the description is incomplete. It doesn't specify the return structure, the behavior with multiple filters, or the relationship to sibling tools. An agent would not know whether this returns all dysfunctions by default or how to combine filters correctly.
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 only 50% (axis and self_report_reliability have descriptions; category and confidence do not). The description merely lists the filter names without adding semantic detail, failing to compensate for the missing schema descriptions of the enum-only parameters.
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 returns a filtered list of dysfunctions and enumerates the filterable fields (axis, self_report reliability, confidence, category). It is distinct from siblings like list_axes (which lists axes) and get_dysfunction (which fetches a single item), though it doesn't explicitly name these alternatives.
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 choose this tool over alternatives. It doesn't mention scenarios where differential_diagnosis or get_probe would be more appropriate, nor does it state any exclusions or conditions for use.
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.