TRIP 2 Implement logo

TRIP 2 Implement

Community
PiLastDigit
TRIP-2-implement

Implement a feature following TRIP plan

Overview

PublisherPiLastDigit
RepositoryTRIP-workflow
Skill nameTRIP-2-implement
Stars
636
Forks
91
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by PiLastDigit on GitHub. Read the source before you install it.

Installation

Install the TRIP 2 Implement AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/PiLastDigit/TRIP-workflow/tree/master/skills/TRIP-2-implement
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/PiLastDigit/TRIP-workflow.git /tmp/TRIP-workflow
mkdir -p .claude/skills
cp -r /tmp/TRIP-workflow/skills/TRIP-2-implement .claude/skills/TRIP-2-implement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable TRIP 2 Implement in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads TRIP 2 Implement on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so TRIP 2 Implement is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Implementation Mode

You are now in implementation mode for [PROJECT_NAME].

Prerequisites - Read First

Before implementing, you MUST read ALL THE LINES of:

  1. @docs/ARCHI.md - Understand current system architecture

Your Task

Implement: $ARGUMENTS


Step 0: Create a Branch (Pre-Implementation)

Always create a dedicated branch before implementing — no need to ask. TRIP-3-release merges it back into the main branch with fast-forward, keeping a single clean linear history.

bash
git checkout -b feat/[short-description]   # or fix/[short-description]

Derive the short description from the plan/feature name. If already on a dedicated branch for this work (e.g., resuming a session), continue on it.


Implementation Phase — Delegate to Codex

You do NOT write the implementation yourself — delegate it to Codex via the codex-implement skill. (Exception: trivial unplanned changes of a few lines may be done directly.)

Delegation is batched: Codex implements a few of the plan's checkboxes per turn, you review and fix each batch, then request the next one with your corrections attached. Same persistent thread throughout — context and conventions compound across turns.

1. Read the plan and decide the batches

Read the plan fully and split its to-dos into batches. You are the judge of batch size:

  • A batch is the smallest set of checkboxes that leaves the tree green (compiles, lints). Never split an interface from its implementation and wiring.
  • The plan is likely sliced vertically: batch within the plan's phase order, never spanning phase boundaries; where possible, prefer a batch that completes a thin end-to-end path over one that builds out a single layer.
  • Target a reviewable diff — roughly ≤300 changed lines per batch. A checkbox that alone exceeds this becomes its own batch.
  • Size by risk: novel, architectural, or security-critical work → small batches (down to one checkbox). Mechanical, repetitive work → larger batches.
  • One-shot escape hatch: a low-risk plan (or phase) of ≤3-4 checkboxes is delegated whole — no batching ceremony.
  • Filter out non-Codex items: checkboxes needing human input, dashboard/console access, credentials, or ops actions are yours — resolve them with the user before or between batches, never delegate them.

2. Delegate batch by batch

Start the session with the first batch (state dir is handled by the script):

bash
bash .claude/skills/codex-implement/scripts/start.sh \
    --prompt-file .claude/skills/codex-implement/prompts/implement.tpl \
    <plan-path> "Implement only: <batch-1 checkboxes>"   # or omit instructions to one-shot a small plan

Each next batch resumes the same thread, carrying your review corrections as --notes:

bash
bash .claude/skills/codex-implement/scripts/resume.sh \
    --prompt-file .claude/skills/codex-implement/prompts/continue.tpl \
    --notes "<what you fixed after the last batch and why; conventions to apply from now on>" \
    <plan-path> "Now implement: <next batch checkboxes>"

Parse the trailing tag of each report:

  • IMPLEMENTATION_COMPLETE → review the batch (below).
  • IMPLEMENTATION_PARTIAL → read the report; resume with instructions for the remainder, or finish small leftovers yourself during the batch review.

3. Review each batch (delta review)

After each Codex report, before requesting the next batch:

  1. Review the delta only: git status -s && git diff — worktree vs index shows just this batch, since previous batches are staged (step 4). Check it against the plan, ARCHI.md patterns, and project conventions (DRY, KISS, comment discipline, error-handling and naming conventions from ARCHI.md).
  2. Fix problems directly yourself — no back-and-forth with Codex over fixes. What you fixed and why becomes the --notes of the next resume.
  3. Micro-gate: run the lint and typecheck/build commands from the Testing Gate (fast checks only — tests wait for the gate itself). Fix failures now.
  4. Checkpoint: git add -A — stage the reviewed batch so the next delta review starts clean. No commits — history stays clean for release.
  5. Verify the plan checkboxes Codex ticked match what the diff actually contains; cross any it completed but missed.

Adapt as you go: clean batch → grow the next one; heavy corrections → shrink the next one and spell out the fix pattern in the notes. If Codex ignores notes or repeats corrected mistakes late in a long session, reset the thread at the next batch boundary — the plan file plus a summary note rebuilds context.

4. Final pass

After the last batch, read the full feature diff once (git diff HEAD). Batch reviews catch local issues; this pass catches cross-batch drift — duplicated helpers, divergent naming, dead code left by course corrections. Fix directly.

The testing gate and Codex code review run once, after the final pass — never per batch. Proceed to the testing gate once you consider the implementation good for review.


Testing Gate

After implementation, before the Codex review loop. Any failure here blocks the loop from starting.

1. Lint, type-check & build

bash
# [ADAPT_TO_PROJECT: Replace with actual lint/type-check/build commands during Init]
[LINT_COMMAND] 2>&1 | tee /tmp/_trip2-lint.txt
[TYPECHECK_COMMAND] 2>&1 | tee /tmp/_trip2-typecheck.txt

2. Run affected unit tests

bash
[TEST_COMMAND] <pattern-for-affected-files>

Only the files/areas the change touched — never the full suite by default.

3. Integration impact check

If the change modifies an externally observable contract (API shape, UI selectors, auth behavior), exercise it with the project's integration/E2E tooling. Docs-only changes skip this.

4. Author missing tests

If the change adds new logic, write its tests now, guided by the plan's Test Impact section and the project's testing guide (see TRIP-test). If no new logic was added, skip this step.

Hard-to-cover code policy:

  • Test observable behavior (inputs → outputs/persisted effects), never internal wiring.
  • Mock-pain tripwire: if the mock setup grows longer than the test's assertions, stop fighting it — check the project's testing guide for a seam recipe; if none applies, skip the deep unit test and add one line to docs/4-unit-tests/COVERAGE-DEBT.md (path | why hard | escape plan).
  • Critical-path floor: behavior touching auth, deletion, persistence, cost, or external request shape must keep at least one behavioral test or manual integration check — coverage debt may defer internal-path depth, never safety-critical behavior.
  • Never hide untested code (no coverage-ignore comments, no config exclusions, no lowering coverage gates). Legacy modules outside the change scope are not a feature blocker — but record newly encountered risky gaps in the ledger.

5. Build the summary

Format: lint: clean | typecheck: clean | tests: N passed (M new)

Fix failures before starting the loop.


Codex Code Review

Always run the Codex code review after the testing gate passes — no confirmation needed.

Loop

The code-review wrappers pin their own state dir — no export needed:

  1. Start:

    bash
    bash .claude/skills/codex-code-review/scripts/start.sh \
        --prompt-file .claude/skills/codex-code-review/prompts/start.tpl \
        <plan-path> "$GATE_SUMMARY"

    $GATE_SUMMARY is the testing-gate summary (lint | typecheck | tests). For unplanned work (no F_*.plan.md), pass a free-form label instead of a plan path.

  2. Parse trailing tag: APPROVED -> synthesize. NEEDS_REWORK -> surface to user. REQUEST_CHANGES -> continue.

  3. Address findings — quote each with file:line, read the actual code, fix legitimate ones, push back on incorrect ones. Critical/Major block approval; Minor/Suggestion are case-by-case.

  4. Write implementer notes (1-3 sentences): which findings you fixed, which you pushed back on and why, any user decisions or environment limitations Codex should stop re-flagging.

  5. Resume (re-run the testing gate first — lint, typecheck, affected tests — and build a fresh summary):

    bash
    bash .claude/skills/codex-code-review/scripts/resume.sh \
        --prompt-file .claude/skills/codex-code-review/prompts/resume.tpl \
        --notes "Fixed X. Pushed back on Y because Z." \
        <plan-path> "$GATE_SUMMARY"

    Loop to step 2.

  6. No cap — keep iterating until Codex returns APPROVED.

Synthesize

Skip if loop converged on Turn 1 (state file already holds full review).

Turn-N state files hold only that turn's delta. After multi-round convergence, produce a consolidated review:

bash
bash .claude/skills/codex-code-review/scripts/resume.sh \
    --prompt-file .claude/skills/codex-code-review/prompts/synthesize.tpl \
    <plan-path> "Today's date is YYYY-MM-DD"

Outputs PROMOTION_READY sentinel. <x.y.z> Version placeholder left unfilled (resolved during TRIP-3-release).

Edge case:

  • User skipped Codex: no synthesis. The CR is written manually during TRIP-3-release: "Code review skipped — trivial change."

Operating Notes

Surface reviews verbatim. Keep edits scoped. If Codex repeats a finding, re-read carefully — you likely addressed an adjacent concern. Reset thread only if context is confused. The testing gate (lint, typecheck, affected tests) must pass before APPROVED.


Handoff to Release

After Codex converges (or is skipped):

  • Cross the corresponding checkboxes in the plan todo list (if any)
  • Then use the AskUserQuestion tool to ask:
    • Question: "Is the implementation complete?"
    • Options: "Yes, everything is complete" (proceed to release), "No, there are remaining items" (continue working)

If "Yes": proceed directly into the release — read .claude/skills/TRIP-3-release/SKILL.md and follow it in this session, passing the same plan path (or feature label). The release skill owns everything from version bump to the fast-forward merge and push.

If "No": continue working, then repeat the sequence: testing gate → Codex review → this question.

Frequently asked questions

What does the TRIP 2 Implement AI skill do?

Implement a feature following TRIP plan

Why use TRIP 2 Implement on TypingMind?

Because you install it once and use it with any model. TRIP 2 Implement is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install TRIP 2 Implement in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PiLastDigit/TRIP-workflow/tree/master/skills/TRIP-2-implement. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use TRIP 2 Implement?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with TRIP 2 Implement?

As many as you like. As long as a model supports skills, you can use TRIP 2 Implement with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the TRIP 2 Implement AI skill free?

It is published on GitHub by PiLastDigit. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇