The derived inventory of exact model-reader, tokenizer and other instrument identifiers in the public evidence corpus, including structured provenance, model-digest and manifest-carried positive-control qualification coverage. Qualification is configuration- and expiry-bound; it does not infer model families, training-data exposure, ownership or independence.
| 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?
With no annotations, the description carries the full burden of behavioral disclosure. It meaningfully explains that qualification is 'configuration- and expiry-bound' and explicitly states what the tool does not infer: 'model families, training-data exposure, ownership or independence.' This goes beyond a simple inventory claim and helps set expectations.
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 compact and front-loaded with the core purpose. It is jargon-heavy, but the two sentences each earn their place: the first states what the tool returns, the second clarifies important limitations.
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 no-parameter, no-output-schema, no-annotation tool, the description is largely complete: it specifies the subject matter, included data dimensions, and boundaries. It does not detail return format or pagination, but the low complexity and clear scope make this a minor gap.
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 zero parameters, so there is little for the description to add beyond schema coverage. The description still usefully clarifies the scope of the returned data (identifiers, provenance, qualification coverage), which is the relevant semantic context for a parameterless call.
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 identifies the resource ('exact model-reader, tokenizer and other instrument identifiers') and positions it as a 'derived inventory' of the public evidence corpus, which distinguishes it from sibling get_* tools. It lacks an explicit verb like 'lists' or 'returns,' relying on the noun phrase and tool name, but the intent is unambiguous.
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 provides no guidance on when to use this tool versus alternatives, and it does not mention any exclusions or preferred sibling tools. An agent would need to infer usage from the tool name and general context.
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.
Most tools have unique resource nouns, but several clusters overlap in purpose: get_progression, get_decisions, get_queue, and get_dispute_triage all describe next-action/status views, and the flagship/runbook/register families require careful reading to distinguish. The detailed descriptions help an agent choose correctly, but boundaries are not always obvious.
There is a strong get_/list_ convention for reads and imperative verbs for writes, making the set largely predictable. Minor deviations such as whoami, how_to_participate, my_suggestions, propose, and second break the pattern slightly but do not make names chaotic.
47 tools is far beyond the well-scoped band and will overwhelm an agent's tool-selection surface. Even if the domain is complex, many read-only projections could be consolidated into fewer parameterized tools.
The core lifecycle is well covered: propose, second, measure, vote, withdraw/replace, retract, and attempt management are all present, with extensive read support. Minor gaps exist around explicit recertify/dispute-settlement write tools and there is no direct edit operation, but the existing supersession/correction mechanisms largely cover those needs.
