Create one immutable repository DecisionPlan revision from a workspace evidence bundle, resolving snapshot_id from triage when omitted.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | ||
| snapshot_id | No | ||
| repository_id | Yes | ||
| workspace_evidence_bundle_ref | 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?
The description discloses immutability and the automatic resolution of snapshot_id from triage, which are useful behaviors. However, with no annotations provided, the agent lacks information on safety (e.g., mutability, side effects) and other important traits like idempotency or failure scenarios.
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 concise sentence that front-loads the core action. Every part adds value, and there is no redundant or irrelevant information.
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 4-parameter tool with no output schema, the description is too brief. It does not explain what a DecisionPlan is, what constitutes a workspace evidence bundle, or what the tool returns upon success. This omits critical context needed for an agent to correctly invoke and interpret results.
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 description adds minimal meaning to parameters beyond their names. It explains that snapshot_id can be omitted and resolved, but does not clarify the purpose of 'model' or the format of 'repository_id' and 'workspace_evidence_bundle_ref'. With 0% schema description coverage, the agent relies heavily on this description, which is insufficient.
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 verb (Create), the specific resource (immutable repository DecisionPlan revision), and the source (from workspace evidence bundle). It also mentions the behavior of resolving snapshot_id from triage when omitted. However, it does not explicitly distinguish this from sibling tools like 'plan_decision' or 'create_repository_snapshot', slightly reducing clarity.
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, nor does it specify prerequisites or conditions. Without explicit context, an agent may not know when to choose this over similar creation tools.
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 target distinct resources or actions, but there is some overlap (e.g., run_repository_fix vs run_repository_pipeline vs simulate_repository) that could cause confusion. Overall, descriptions help differentiate.
Tool names are primarily snake_case with a verb_noun pattern, but there are inconsistencies (e.g., single-word verbs like 'simulate', 'tokenize', and mixed prefixes like 'preview_', 'product_'). The pattern is readable but not uniform.
With 140 tools, the server is extremely over-scoped for typical MCP usage. This overwhelms agents and suggests poor separation of concerns, likely violating the principle of minimal tool surfaces.
The tool set covers a wide range of functionalities including data onboarding, simulation, decisions, repository management, and admin operations. Minor gaps exist (e.g., no update_agent_run), but core workflows are well-supported.
