by Vuk97
Stop your coding agent from stalling real work on self-invented bookkeeping - receipts, hashes, locks, certification rituals. Ship first, then verify. Skill for Claude Code, Codex, and other agents.
# Add to your Claude Code skills
git clone https://github.com/Vuk97/forward-implementation-firstGuides for using ai agents skills like forward-implementation-first.
forward-implementation-first is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Vuk97. Stop your coding agent from stalling real work on self-invented bookkeeping - receipts, hashes, locks, certification rituals. Ship first, then verify. Skill for Claude Code, Codex, and other agents. It has 107 GitHub stars.
forward-implementation-first's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/Vuk97/forward-implementation-first" and add it to your Claude Code skills directory (see the Installation section above). forward-implementation-first ships a SKILL.md manifest, so compatible agents can discover and load it automatically.
forward-implementation-first is primarily written in Shell. It is open-source under Vuk97 on GitHub, so you can review or fork the full source.
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Build working capability and correct output before administrative bookkeeping. Apply this contract both while building a system and while running it.
This skill applies to:
It applies whether the action runs through a full orchestrator, a focused command, or a manual stage invocation.
Before each action, classify it as one of:
Choose categories 1 and 2. Skip category 3 unless the user asks for it or the artifact is itself part of the product. When administrative work blocks a path without protecting correctness, remove that dependency from the path.
A stage may move backward or be replayed only when at least one real condition holds:
Missing or stale administrative metadata is not one of those conditions.
When the orchestrator refuses to run a stage only because of a receipt, certification marker, progress record, administrative hash, or lock:
Do not refuse an authorized manual run because the full pipeline cannot issue a receipt. Do not push the user toward another agent or tool to get around your own bookkeeping.
Use the checks that match the change:
Hashes may identify inputs or revisions, but they never grant correctness, execution, or roadmap credit.
Bookkeeping is cheap to skip. Evidence is not. Keep these:
Report implemented behavior and measured output first. List blockers literally. Keep infrastructure progress separate from evidence about the output. Do not turn administrative completion into a substitute for working capability.
An agent skill that stops a coding agent from getting stuck servicing its own paperwork.
Long-running agent pipelines grow bookkeeping: content hashes, lock files, "receipts" that prove a stage ran, certification markers, dashboard rows, progress metadata. None of that is the product. All of it is easy for a model to mistake for the product. Once that happens the agent stops shipping and starts curating, and you pay full price for an agent that produces nothing you asked for.
This skill gives the agent one classification to make before every action, and a short list of things it is never allowed to do. It is about 150 lines of Markdown. It is model-agnostic, tool-agnostic, and domain-agnostic.
You have a pipeline with ordered stages. Stage 40 produces a file that stage 41 consumes. Somewhere along the way the orchestrator also writes a small JSON record saying stage 40 completed, with a hash of its inputs.
Then you change one producer. The hash no longer matches. Here is what an agent does without this skill:
Nothing in that sequence is stupid in isolation. Each step is a defensible local decision. Together they cost days, and the output at the end is identical to the output you already had. The pathology is that administrative metadata is being used as a proxy for correctness, and the proxy is both cheaper to check and completely uninformative.
The second half of the failure mode is worse: the agent tells you it cannot proceed. You then go run the stage yourself, or open a second agent to do it, and the first agent sits there guarding a hash.
Before each action, the agent classifies it as one of three things:
Do 1 and 2. Skip 3 unless the user asks for it, or the artifact is part of the product. When category 3 blocks a path without protecting correctness, delete the dependency.
That is the whole idea. The rest of SKILL.md makes it hard to weasel out of, because a model that wants to do bookkeeping will find a reason.
This is the part that makes the skill safe to install, and the part most "just move faster" prompts get wrong. Bookkeeping is cheap to skip. Evidence is not. The skill explicitly preserves:
An execution record that carries the command, the input, the result, and the expectation it was checked against is real evidence. Its absence blocks the claim it supports. It does not retroactively invalidate an unrelated stage twenty steps back. That distinction is the whole difference between rigor and superstition, and it is the line the skill draws.
A pipeline stage may be replayed or rolled back only for a real reason:
Missing or stale metadata is not on that list. When a stage is blocked only by a marker, the agent runs it manually, validates the output, publishes it, continues from the cursor, and then removes the administrative-only gate so the same block cannot happen again. Replay the smallest affected cone, not the whole history.
The skill also covers parallelism, because the two problems show up together. An agent that is busy with bookkeeping usually also serializes everything.
The last two points matter more than the speedup. Cheap parallel workers are useful precisely because they are not trusted, and the value disappears the moment their output is merged without a check.
The skill is a single Markdown file with YAML frontmatter, following the Agent Skills convention. Copy it wherever your agent looks for skills:
git clone https://github.com/Vuk97/forward-implementation-first
cd forward-implementation-first
./install.sh
install.sh copies SKILL.md into every agent skill directory it finds:
| Agent | Path |
|---|---|
| Claude Code | ~/.claude/skills/forward-implementation-first/ |
| Codex | ~/.codex/skills/forward-implementation-first/ |
| Shared convention | ~/.agents/skills/forward-implementation-first/ |
For a project-scoped install, copy the directory to .claude/skills/ or
.agents/skills/ in the repo instead. Restart the agent afterward. Running
sessions do not reload skills.
A skill is a suggestion. The model decides whether to load it. If your agent supports always-on rules or hooks, put the decision rule there too, because this particular failure mode is one the model walks into confidently.
Install it if any of these describe your setup:
Common shapes: staged data and ETL runs, large code migrations, build and release pipelines, documentation generation over many inputs, batch analysis jobs, and any roadmap an agent works through over days.
Skip it for single-shot tasks, short interactive sessions, and any workflow where the audit trail is the deliverable. If someone is going to read your receipts, they are not bookkeeping.
This started as a prompt pasted at the top of every session in a long-running staged pipeline, where the agent had repeatedly invalidated dozens of completed stages over metadata drift and then declined to run stages by hand. Pasting it every time worked. Forgetting to paste it cost days.
Turning it into a skill made the behavior default instead of remembered.
MIT. See LICENSE.