Simulate repository patch risk and return the gated DecisionEnvelope, resolving snapshot_id from the decision plan when omitted.
| Name | Required | Description | Default |
|---|---|---|---|
| runs | No | ||
| seed | No | ||
| snapshot_id | No | ||
| repository_id | Yes | ||
| decision_plan_id | 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?
Annotations are absent, so the description carries the full burden. It only states that the tool returns a 'gated DecisionEnvelope' and resolves snapshot_id, but does not disclose whether the simulation is read-only, requires specific permissions, or has any side effects. Key behavioral traits like idempotency or rate limits are missing.
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 18-word sentence that front-loads the core purpose. There is no redundant or extraneous information—every word contributes to conveying the tool's function.
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?
The tool has 5 parameters, no output schema, and no annotations, yet the description is extremely brief. It does not explain the simulation process, the meaning of 'gated DecisionEnvelope', or the effect of parameters like 'runs' and 'seed'. This leaves significant gaps for effective usage, especially for a complex simulation tool.
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?
Schema description coverage is 0%. The description mentions only the snapshot_id resolution behavior, leaving parameters like 'runs' and 'seed' unexplained. It fails to add meaning beyond the schema's basic types and constraints, which is insufficient for a 5-parameter tool.
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 tool's action ('Simulate repository patch risk') and primary output ('return the gated DecisionEnvelope'). It mentions a specific behavior (resolving snapshot_id from decision plan), but does not explicitly differentiate it from sibling tools like 'simulate' or 'simulate_repository_patch', leaving ambiguity about when to use this one over others.
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?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'simulate', 'simulate_repository_patch'), the absence of usage context forces the agent to rely solely on the name, which is insufficient for correct selection.
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.
