agentleFS
guerrilla2799guerrilla2799/ops-and-scale-os/skills/artifact-eval/SKILL.md

artifact-eval

Skill1 starsChanged 3 months agoMITView on GitHub

The output gate for this repo. Runs on any deliverable before it is handed over, and also when the user says "review this deliverable", "is this ready", "check this before I send it", "quality check". Verifies the artifact is complete, honest about its assumptions, and free of the specific failures each artifact type is prone to. Returns a receipt. Gates deliverables this repo produced. To score your own AI system output against a rubric, with a separate judge and a logged cycle, use `eval-loop`.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before handing over any audit, model, spec, or plan produced by this repo

    line 12
  2. Distinctive:

    Before any number reaches a slide

    line 13
  3. Distinctive:

    When somebody asks whether a deliverable is ready

    line 14
  4. Distinctive:

    Every borrowed rate, estimate, and benchmark is labeled as such, inline, where it is used rather than in a footnote.

    line 63
  5. Distinctive:

    A gate trip blocks handover: No score absorbs a gate

    line 84
  6. Distinctive:

    Borrowed benchmarks are labeled at the point of use,: not in a footnote

    line 86
  7. Distinctive:

    The unwelcome part must be present: No do-not-do list means it was softened

    line 88

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Artifact Eval

The last thing that runs. Checks the deliverable against the failures its type is prone to, and refuses to hand over work that is quietly incomplete.

When to use

  • Before handing over any audit, model, spec, or plan produced by this repo
  • Before any number reaches a slide
  • When somebody asks whether a deliverable is ready

Inputs

  • Reads: the artifact, plus its source skill's rules section
  • Needs from user: who the audience is, and whether any number in it is going to a board

Workflow

1. Run the universal gates

Any trip is a fail, regardless of how good the rest is.

GATE 1  An unsourced number. Every figure has a provenance or is marked [unverified]
GATE 2  A borrowed benchmark presented as this company's own data
GATE 3  A recommendation with no stated cost, owner, or date
GATE 4  A customer-specific metric or logo with no clearance marker
GATE 5  A conclusion the stated evidence does not support
GATE 6  Prose that has not passed writing-quality

Gate 2 is the one that slips most. A benchmark table copied into a client deliverable becomes their number by the second reading, and nobody can find where it came from by the third.

2. Run the type-specific check

ArtifactThe failure it is prone to
Systems auditEight problems and no single constraint. Interviews with no diagnostics run
Object modelNo named decision maker on the four definitions
Scoring modelThresholds set before the distribution was seen. No discrimination test
Waterfall specPaid columns not structurally downstream of the free gate
Signal taxonomyA signal with no decay window, or a play that says "notify"
Agent briefBlank kill criterion. No named accountable user
GuardrailsEvery guardrail is advisory. Nothing placed where persuasion cannot reach
Eval specAnchors missing. No frozen calibration set
Stack auditSavings claimed with no capability lost named
Attribution modelSourced and influenced summed. Window chosen after results
LifecycleStages defined as entries. No max time in stage
Metrics dictionaryMissing object counted, date field, filters, or exclusions
Cost forecastNo actual-against-forecast comparison after the run

3. Check completeness against the source skill

Open the source skill's Output section. Every file it says it writes must exist, and every item it says it prints must be present.

A deliverable missing a section its own skill promised is the most common quiet failure, and it is trivially checkable.

4. Check the assumptions are surfaced

Every borrowed rate, estimate, and benchmark is labeled as such, inline, where it is used rather than in a footnote. A reader must be able to tell at the point of reading which numbers are theirs and which are borrowed.

5. Check that the unwelcome part is present

Most skills in this repo require something the audience will not enjoy: a do-not-do list, a named capability loss, a refusal, a kill criterion, a stated constraint. If the deliverable has none, it was probably softened during writing.

An audit with no bad news is not an audit.

6. Return the receipt

artifact-eval: <type>, gates <pass | GATE n tripped>,
  completeness <n/n sections>, assumptions labeled <yes | no>
writing-quality: <receipt from that skill>

Output

  • Returns the artifact, or a list of what must be fixed before it can be handed over
  • Prints the receipt

Rules & quality bar

  • A gate trip blocks handover. No score absorbs a gate
  • Every number is sourced or marked [unverified]
  • Borrowed benchmarks are labeled at the point of use, not in a footnote
  • Completeness is checked against the source skill's own Output section
  • The unwelcome part must be present. No do-not-do list means it was softened
  • Both receipts appear, or the gates did not run
  • Never pass work with a promised section missing. Name it and send it back

Related skills

  • Runs: writing-quality as its first gate
  • Applies to: every deliverable in this repo

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.