athola/proof-of-work
Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.
npx skills add https://github.com/athola/claude-night-market --skill proof-of-work
> "It looks correct" is not "I verified it works."
> Proof-of-work is the discipline of closing that gap:
> reproducible evidence before any claim that a task is done.
imbue:karpathy-principles)imbue:scope-guard)The "Proof of Work" methodology prevents premature completion claims by
requiring technical verification before stating that a task is
finished. For example, instead of assuming an LSP configuration
functions after a restart, we verify that the server starts and that
tools respond to queries. This approach confirms the solution works
before the user attempts validation.
Before claiming completion, provide reproducible evidence of the
solution's performance and address edge cases. All claims must be
backed by actual command output captured in the current environment.
NO IMPLEMENTATION WITHOUT A FAILING TEST FIRST
NO COMPLETION CLAIM WITHOUT EVIDENCE FIRST
NO CODE WITHOUT UNDERSTANDING FIRST
The Iron Law prevents testing from becoming a perfunctory exercise. If
an implementation is planned before tests are written, the RED phase
fails to drive the design. Understand the technical rationale for an
approach and its limitations before declaring it done. Before writing
code, document evidence of the failure being addressed and confirm
that tests are driving the implementation.
Verify the fundamentals of the implementation and the reasons for
choosing it over alternatives. Identify where a solution might fail
rather than stating it should always work. The TDD cycle follows these
mandatory steps:
| Self-Check Question | If Answer Is Wrong | Action |
|---------------------|-------------------|--------|
| Do I have documented evidence of failure/need? | No | STOP, document failure first |
| Am I testing pre-conceived implementation? | Yes | STOP, let test DRIVE design |
| Am I feeling design uncertainty? | No | STOP - uncertainty is GOOD |
| Did test drive implementation? | No | STOP - doing it backwards |
proof:iron-law-red: Failing test written before implementation.proof:iron-law-green: Minimal implementation passes test.proof:iron-law-refactor: Code improved without behavior change.proof:iron-law-coverage: Coverage gates passed (line, branch, and mutation).Confirm that work passes all line, branch, and mutation coverage
gates. For detailed enforcement patterns, see
iron-law-enforcement.md.
Apply this skill before stating that work is "done," "finished," or
"ready." Use it before recommending solutions or stating that a
configuration "should work." Stop if you find yourself assuming a
configuration is correct without testing it or recommending a fix
without first reproducing the problem. Red flags include thinking
"this looks correct" without actual verification. If you cannot
explain each line of a configuration or why a specific practice
applies to the current context, the necessary validation steps have
been skipped.
proof:problem-reproduced)Before proposing a solution, verify the current state. Use tools like
ps, echo, and cat to check running processes, environment
variables, and configuration files. Document the failure with command
output and error logs.
proof:solution-tested)Before claiming a solution works, execute it in the current
environment. Capture the actual output and confirm that it matches
expected behavior. Do not rely on assumed output.
proof:edge-cases-checked)Research known bugs and limitations related to the approach. Check
GitHub issues, version compatibility, and official documentation to
identify potential blockers or common pitfalls.
proof:evidence-captured)Use imbue:proof-of-work to document the commands executed, their
output, timestamps, and the conclusions drawn from each step.
proof:completion-proven)Define acceptance criteria and validate each item. If a blocker is
identified, document the diagnosis with evidence and provide
workaround options instead of claiming completion.
Use proof-of-work to validate improvement opportunities identified by
/update-plugins or /fix-workflow. Document the baseline metrics
(step count, failure rate, duration), test the proposed changes, and
capture the improved metrics to demonstrate quantitative impact.
Verify that the problem was reproduced with evidence and the solution
was tested in the actual environment. Research known issues and
consider edge cases. Capture evidence in a reproducible format and
confirm that all acceptance criteria are met. The completion statement
must detail the specific tests run and their results, citing evidence
for each claim.
Before sending a completion message, confirm that you have run the
recommended commands and captured their output. Verify that you have
researched known issues and that the validation steps are reproducible
by the user. Ensure you are proving rather than assuming.
conventions and safe deletion rules for imbue TodoWrite items
evidence capture, audit trails, and reproducibility patterns
high-stakes changes, why the producing agent may not be its own
sole verifier, and what counts as an independent check
check is real at all: validate the spec separately, prove the check
fails when behavior breaks (mutation/revert), prefer executable and
property-based checks over an LLM judge
imbue:karpathy-principles: the "Goal-Driven Execution" principlewraps the Iron Law in a four-principle synthesis useful as a
pre-flight gate
docs/quality-gates.md#skill-level-quality-gate-composition forthe full gate-skill federation graph
(proof:iron-law-red, proof:iron-law-green) confirming
test-first execution.
[E1]/[E2] evidence reference exists in theresponse, backed by a real command invocation and its output.
verified by running, not by inspection.
next concrete step to unblock it.
correct", or "will work" claims without supporting evidence.
Take athola/proof-of-work from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.