Discover AFMR resources
discover_afmrReturn canonical AFMR specifications, registries, schemas, endpoints, and scope boundaries.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
discover_afmrReturn canonical AFMR specifications, registries, schemas, endpoints, and scope boundaries.
| 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 readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds context by specifying exactly what is returned: 'specifications, registries, schemas, endpoints, and scope boundaries.' This goes beyond annotations to clarify the scope of information provided, which is important for the agent to understand the tool's behavior. No contradictions.
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 sentence that front-loads the action ('Return') and resource details. Every word is informative, with no wasted or redundant phrasing. It achieves maximum clarity with minimal length.
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 tool has no parameters, no output schema, and rich annotations, the description covers the key return categories (specifications, registries, schemas, endpoints, scope boundaries). It is moderately complete, though it could be slightly enhanced by specifying the expected format (e.g., JSON object) or that the response is exhaustive due to openWorldHint=false. However, the current level is adequate for agent understanding.
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?
The tool has 0 parameters with 100% schema coverage, so the baseline is 4 per the rubric. The description does not need to add parameter information since there are none, and it does not repeat schema details. The score reflects that no additional value is needed for 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 uses the specific verb 'Return' and resource 'canonical AFMR specifications, registries, schemas, endpoints, and scope boundaries,' clearly stating the tool's action and output. It effectively distinguishes from sibling tools like 'get_lift_evidence_contract' and 'lookup_failure_mode' which retrieve specific contracts or failure records, while 'discover_afmr' provides a broad, canonical overview.
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 does not explicitly state when to use this tool versus its siblings or when not to use it. However, given its read-only and comprehensive nature (openWorldHint=false), it is implied that it should be used when a complete canonical reference of AFMR resources is needed. No exclusions or alternatives are provided, leaving some ambiguity for the agent.
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 has a clearly distinct purpose: one returns canonical AFMR specs, two return specific contracts (lift evidence and reputation attestation), and one looks up failure modes. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern with snake_case: discover_afmr, get_lift_evidence_contract, get_reputation_attestation_contract, lookup_failure_mode. No deviations or mixed conventions.
Four tools are well-scoped for a discovery service. Each tool earns its place, covering key functions without being too few or too many.
The tool set covers the main aspects of AFMR discovery: general specs, two key contracts, and failure mode lookup. There are no obvious gaps for the stated domain.