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Stride — AI software delivery platform

Reanalyze legacy system

stride.trigger_legacy_reanalysis

Re-ingest a legacy system's connected repository (Modernize). Refuses when the repo is not stale unless force:true (spends AI credits). Incremental by default; pass full:true to re-analyze every chunk.

Input Schema

NameRequiredDescriptionDefault
fullNoFull re-ingest instead of incremental dirty-chunks only.
forceNoRe-analyze even when the repo is up to date.
legacySystemIdYesUUID of the legacy system.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Adds real context beyond the annotations: the staleness gate, that force spends AI credits, and the incremental vs full trade-off. It does not say whether the call blocks or returns a job handle, which matters for a non-idempotent, open-world operation that likely runs asynchronously.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with what it does, then the refusal gate, then the mode default. No filler; each sentence carries a distinct constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a non-idempotent, billable, open-world mutation with no output schema, the definition never says what comes back (job id, status handle, or synchronous result) or how progress is observed via get_tool_call_status. Everything else an agent needs to invoke it is present, so this is adequate but with a clear gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description earns an extra point by explaining the cost consequence of force ('spends AI credits') and contrasting full vs dirty-chunk re-analysis rather than merely restating the flags.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: re-ingest a legacy system's connected repository for Modernize. The 'Refuses when the repo is not stale' clause implicitly points at the status-check sibling, but no sibling is named, so the differentiation is soft rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear when-not condition ('refuses when the repo is not stale unless force:true') and a mode decision rule (incremental by default, full:true for everything). It stops short of naming the alternative step (e.g. check get_modernization_repo_status first) or stating prerequisites like permissions.

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

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