simulate_repository_patch
Simulate an in-flight repository patch and return the canonical repository envelope.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| confidence | No | ||
| patch_diff | Yes | ||
| snapshot_id | Yes | ||
| repository_id | Yes |
Simulate an in-flight repository patch and return the canonical repository envelope.
| Name | Required | Description | Default |
|---|---|---|---|
| confidence | No | ||
| patch_diff | Yes | ||
| snapshot_id | Yes | ||
| repository_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?
No annotations provided, so description should disclose behavioral traits. It implies a read-only simulation but does not state side effects, permissions, or what 'canonical repository envelope' means. Lacks sufficient behavioral context.
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?
Single-sentence description is concise but lacks necessary detail. Every word contributes to purpose but fails to provide adequate structure for agent use.
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 4 parameters, no output schema, and no annotations, the description is incomplete. It does not cover parameter semantics, return format, or behavioral traits needed for correct invocation.
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%, and the description does not explain any parameters. The agent must infer meaning solely from parameter names like repository_id, snapshot_id, patch_diff, and confidence, 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?
Description clearly states it simulates an in-flight repository patch and returns a canonical repository envelope. The verb 'simulate' and resource 'repository patch' are specific, but it does not explicitly differentiate from sibling tools like 'simulate_repository' or 'apply_repository'.
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 on when to use this tool versus alternatives, no prerequisites or constraints mentioned. The description is too brief to convey usage 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 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.