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TRWMCP Tools Reference

MCP tools reference

MCP tools are the low-level primitives your AI uses while it works. You usually do not type them directly; they show up in activity traces as the agent loads memory, checkpoints progress, verifies quality, and closes the session. TRW registers 45 MCP tools for agent use; this page walks through the most common ones, grouped by what they do, so you can tell what the agent is doing and why. Any one session sees a narrower set than that — the server advertises tools per task type by default, which the quick reference below explains.

Quick reference

The most common tools at a glance — the ones you will see most in everyday sessions. The Phase column shows where each tool typically belongs in the six-phase lifecycle.

This page curates a selected set out of the 45 tools the trw-mcp server registers for agent use. Expect your client’s MCP tool listing to show fewer than that, not all of them. By default (tool_resolution_mode: standard) the server advertises only the tools the current task type needs, and a call to a tool outside that set is refused with tool_not_in_surface rather than executed. An agent requests one it needs with trw_request_tool_access; setting tool_resolution_mode: all in .trw/config.yaml turns the narrowing off and advertises every tool at once.

trw_session_startInspect
Description
Load prior learnings and recover any active run.
Phase
Research
trw_initInspect
Description
Create a run directory for progress tracking.
Phase
Plan
trw_statusInspect
Description
Show current phase, progress, and next steps.
Phase
Any
trw_checkpointInspect
Description
Save an atomic progress snapshot.
Phase
Implement
trw_pre_compact_checkpointInspect
Description
Emergency checkpoint before context compaction.
Phase
Any
trw_learnInspect
Description
Record a discovery for all future sessions.
Phase
Review
trw_learn_updateInspect
Description
Mark learnings as resolved or obsolete.
Phase
Any
trw_recallInspect
Description
Search past learnings by keyword, tags, or impact.
Phase
Research
trw_instructions_syncInspect
Description
Refresh the client instruction file (CLAUDE.md / AGENTS.md / etc.) with the latest TRW protocol.
Phase
Deliver
trw_build_checkInspect
Description
Record the test, static-check, and coverage results you already ran, for delivery gates. Language-agnostic - it reads your project-native commands, it does not run them.
Phase
Validate
trw_reviewInspect
Description
Independent code review with rubric scoring.
Phase
Review
trw_deliverInspect
Description
Persist learnings, sync artifacts, close run.
Phase
Deliver
trw_prd_createInspect
Description
Generate an AARE-F requirements document.
Phase
Plan
trw_prd_validateInspect
Description
Check requirements quality and completeness.
Phase
Plan
trw_submit_feedbackInspect
Description
Submit a bug report, install issue, feature request, or feedback to the TRW maintainer via the authenticated submissions endpoint.
Phase
Any

Session and workflow

These tools manage one work session. trw_session_start explicitly requests prior learnings and active-run state; checkpoints preserve milestones that a later session can recover after interruption or compaction.

trw_session_startInspect
What it does
Load prior learnings and recover any active run.
When to use
Start of every session
trw_initInspect
What it does
Create a run directory for progress tracking.
When to use
New tasks beyond quick fixes
trw_statusInspect
What it does
Show current phase, progress, and next steps.
When to use
Resuming after interruption
trw_checkpointInspect
What it does
Save an atomic progress snapshot.
When to use
After each milestone
trw_pre_compact_checkpointInspect
What it does
Emergency checkpoint before context compaction.
When to use
Automatically before context window fills

Learning and knowledge

These tools record, retrieve, and update durable discoveries. Recall is explicit and ranked against the current query; instruction sync refreshes the managed TRW protocol rather than silently promoting arbitrary learning text.

trw_learnInspect
What it does
Record a discovery for all future sessions.
When to use
On errors, gotchas, or patterns
trw_learn_updateInspect
What it does
Mark learnings as resolved or obsolete.
When to use
When issues are fixed
trw_recallInspect
What it does
Search past learnings by keyword, tags, or impact.
When to use
Before starting unfamiliar work
trw_instructions_syncInspect
What it does
Refresh the client instruction file (CLAUDE.md / AGENTS.md / etc.) with the latest TRW protocol.
When to use
During delivery or after major discoveries

Quality and verification

Quality tools record validation outcomes, produce structured review artifacts, and enforce the delivery receipt boundary. Run the real project commands first; these tools preserve and evaluate the evidence rather than replacing the test runner.

trw_build_checkInspect
What it does
Record the test, static-check, and coverage results you already ran, for delivery gates. Language-agnostic - it reads your project-native commands, it does not run them.
When to use
After implementation
trw_reviewInspect
What it does
Independent code review with rubric scoring.
When to use
Before committing changes
trw_deliverInspect
What it does
Persist learnings, sync artifacts, close run.
When to use
End of every task

Requirements

Requirements are the bridge between what you want and what your agent builds. These tools create AARE-F compliant PRDs with EARS-format requirements, then validate them for completeness before implementation begins.

trw_prd_createInspect
What it does
Generate an AARE-F requirements document.
When to use
Defining new features
trw_prd_validateInspect
What it does
Check requirements quality and completeness.
When to use
Before implementation begins

Feedback

Send the TRW maintainer a bug report, install issue, feature request, or general feedback without leaving your editor. Submissions go through the authenticated platform endpoint, and PII - license keys, API key prefixes, your home path, and sensitive env vars - is redacted client-side before anything leaves your machine.

trw_submit_feedbackInspect
What it does
Submit a bug report, install issue, feature request, or feedback to the TRW maintainer via the authenticated submissions endpoint.
When to use
When you hit a bug or want to send feedback

Usage examples

A connected agent calls these tools when the workflow requires them. These examples show the activity shape you may see as a task moves from startup to delivery.

Common patterns

Tools combine differently depending on task risk and client capability. Start with the smallest pattern that preserves the evidence and handoff the task actually needs.

MCP resources

In addition to tools, TRW exposes 6 read-only MCP resources. Your AI reads these for configuration, state, and templates without making a tool call. Unlike tools, resources are not filtered by task type — all of them are readable in every session.

Resource
trw://framework/config
What it provides
Current TRW configuration - ceremony mode, trust level, target platforms
Resource
trw://framework/versions
What it provides
Framework and package versions for compatibility checks
Resource
trw://run/state
What it provides
Active run phase, checkpoints, and progress metrics
Resource
trw://learnings/summary
What it provides
Recent high-impact learnings for the current project
Resource
trw://templates/prd
What it provides
PRD requirements-document template (AARE-F)
Resource
trw://templates/shard-card
What it provides
Shard-card scaffold for decomposing larger requirements

Next steps

Tools are the primitives. Skills show the packaged workflows built on top of them, agents show who uses them, and lifecycle explains when each one should appear.

Next

Tools are the primitives. Skills and agents show how TRW composes them into larger workflows and delegated work.