mcp_engram_cold_start_fidelity

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so description must carry behavioral weight. It discloses score range, input dependencies, and alternate emission points, but does not explicitly state whether the call is read-only, modifies state, or requires certain backend readiness, leaving some burden unmet.

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, front-loaded with the core action and output range; the second sentence adds useful alternative emission and ritual context without repetition. Jargon is dense but not bloated.

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?

For a computation with no parameters and no output schema, the description covers purpose, output range, inputs, and alternative sources of the value. Some terms ('mean hub CRS', 'BVH/NVMe') are unexplained, but the essential invocation context is present.

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?

Tool has zero parameters, so schema coverage is trivially 100%. Description adds value by naming the implicit inputs (live continuation, readiness components) even though no formal parameters exist, aligning with the 0-param baseline of 4.

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 a specific verb ('Compute') and names the resource ('cold-start fidelity score'), including the output range and input components. This clearly distinguishes it from sibling tools like process_metrics or verify_manifold_integrity.

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?

It implies the tool is for direct computation of the cold-start fidelity score and notes the same value is emitted on session_start / get_continuation_bundle, giving agents alternative pathways. However, it does not explicitly state when to prefer this tool over those alternatives or exclude other cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.