get_framework_metadataReturns the scoring framework metadata: seven resilience domains, five result bands with score ranges, and the Likert scale definition. No arguments required. Read-only, no PII.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | ||
| domains | Yes | ||
| disclaimer | Yes | ||
| likertScale | Yes | ||
| resultBands | Yes |
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?
No annotations are provided, so the description carries the disclosure burden. It clearly discloses that the call is read-only and involves no PII, which covers the main behavioral concerns for a simple metadata endpoint. It does not mention rate limits or auth, but for this low-complexity tool the disclosure is adequate.
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 two sentences with no filler. It front-loads the exact metadata contents and then adds the no-argument and safety constraints. Every sentence earns its place.
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?
Given the low complexity, empty input schema, and available output schema, the description is complete. It tells the agent what is returned, that no arguments are needed, and that the operation is read-only and PII-free, which is sufficient for correct invocation.
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?
There are zero parameters and the schema is an empty object, so parameter semantics are intentionally trivial. The description explicitly states 'No arguments required', making the no-input expectation unambiguous and adding value beyond the empty schema.
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 ('Returns'), resource ('scoring framework metadata'), and enumerates concrete contents: seven resilience domains, five result bands, and the Likert scale definition. It is clearly differentiated from the sibling run_anchored_hope_index, which is the calculation tool rather than the metadata getter.
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?
The description implies usage ('Returns the scoring framework metadata') and gives useful constraints ('No arguments required', 'Read-only, no PII'), but it does not explicitly state when to use this tool versus run_anchored_hope_index. An agent must infer that this is for definitions rather than score computation.
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.
The two tools have clearly distinct roles: one returns framework metadata and requires no arguments, while the other executes the actual structured reflection/assessment. There is no overlap or ambiguity between them.
Both tools use a consistent snake_case verb_noun pattern: get_framework_metadata and run_anchored_hope_index. The names clearly differentiate metadata retrieval from running the instrument.
Two tools is well-scoped for a dedicated single-instrument server: one to retrieve scoring/framework information and one to run the instrument itself. Each tool is necessary and earns its place.
For the stated domain of an educational hope/resilience reflection tool, the surface is complete: agents can access framework metadata and execute the reflection. No obvious lifecycle or workflow operations are missing given the intentionally limited, non-clinical scope.