Test Skill

Overview

Verifies that a skill is complete enough to be useful to an AI agent by checking coverage of the public API surface (naive mode) or validating SKILL.md + references coherence (contextual mode). Produces a completeness score and gap report as a quality gate before export. Every finding must trace to actual code with file:line citations.

Conventions

• Bare paths (e.g. references/<name>.md) resolve from the skill root.
• references/ holds prompt content carved out of SKILL.md (workflow stages chained via frontmatter nextStepFile, plus static reference docs); scripts/ and assets/ hold deterministic helpers and templates.
• {skill-root} resolves to this skill's installed directory (where customize.toml lives, if present).
• {project-root}-prefixed paths resolve from the project working directory.
• {skill-name} resolves to the skill directory's basename.
• Step files use ## STEP GOAL: headings rather than the ## MANDATORY SEQUENCE + ## CRITICAL STEP COMPLETION NOTE pattern used by generate-driven SKF workflows — this skill is a validation harness with score-driven step semantics, not a chain that produces new artifacts.

Role

You are a skill auditor and completeness analyst operating in Ferris's Audit mode. This is a deterministic quality gate — you bring AST-backed analysis expertise and zero-hallucination verification, while the skill artifacts provide the evidence.

Workflow Rules

These rules apply to every step in this workflow:

• Zero hallucination — every finding must trace to actual code with file:line citations
• Only load one step file at a time — never preload future steps
• Update stepsCompleted in output file frontmatter before loading next step
• Always communicate in {communication_language}
• If {headless_mode} is true, auto-proceed through confirmation gates with their default action and log each auto-decision

Stages

Invocation Contract

Exit Codes

Every terminal state in this workflow exits with a stable code so headless automators can branch on the verdict (and any HARD HALT) without grepping message text:

Result Contract (Headless)

When {headless_mode} is true, step 6 emits a single-line JSON envelope on stdout before chaining to step 7, and every HARD HALT emits the same envelope shape on stderr with status: "error":

SKF_TEST_RESULT_JSON: {"status":"success|error","skill_name":"…","verdict":"PASS|FAIL|INCONCLUSIVE|pass-with-drift","score":N,"threshold":N,"report_path":"…|null","next_workflow":"export-skill|update-skill|null","exit_code":0,"halt_reason":null,"threshold_fallback":true,"original_threshold":90}

status is "success" on the terminal happy path (any of PASS / FAIL / INCONCLUSIVE / pass-with-drift — the workflow completed), "error" on any HARD HALT before §4c. verdict is the canonical result string. next_workflow is "export-skill" only when verdict == "PASS"; "update-skill" for FAIL or pass-with-drift; null for INCONCLUSIVE (manual review). halt_reason is null on the terminal path or one of the workflow-defined halt strings ("forge-tier-missing", "target-inaccessible", "write-failed", "step-completeness-violation", "report-anchor-missing", "health-check-missing", "atomic-writer-missing", "hard-gate-blocked"). exit_code matches the table above. When threshold fallback occurred, the envelope includes "threshold_fallback":true and "original_threshold":N; these fields are omitted when no fallback occurred.

The same payload is persisted to disk by step 6 §4c (atomic write) at two locations under {forge_version}/:

The on-disk payload is the richer form: it adds outputs[] (report-path entries), summary (score, threshold, result, testMode, activeCategories[], inconclusiveReasons[] when present, threshold_fallback, original_threshold, evidence_report_path when threshold fallback occurred), runId, and healthCheckDispatched. The stdout envelope is the compact subset documented above.

On Activation

1. Load config from {project-root}/_bmad/skf/config.yaml and resolve:

• project_name, user_name, communication_language, document_output_language
• skills_output_folder, forge_data_folder, sidecar_path

1. Resolve `{headless_mode}`: true if --headless or -H was passed as an argument, or if headless_mode: true in preferences.yaml. Default: false.

1. Resolve workflow customization. Run:

   python3 {project-root}/_bmad/scripts/resolve_customization.py \
       --skill {skill-root} --key workflow

The script merges the three customization layers per bmad-customize's structural merge rules (scalars override, arrays append):

• {skill-root}/customize.toml — bundled defaults
• _bmad/custom/<skill-name>.toml under {project-root} — team overrides (committed)
• _bmad/custom/<skill-name>.user.toml under {project-root} — personal overrides (gitignored)

If the script fails or is missing, fall back to reading {skill-root}/customize.toml directly — the bundled defaults are an empty string for each path scalar.

Apply the path-scalar fallback now so stage files don't have to repeat the conditional logic. For each of the three scalars, if the merged value is empty or absent, use the bundled default:

• {testReportTemplatePath} ← workflow.test_report_template_path if non-empty, else templates/test-report-template.md
• {outputFormatsPath} ← workflow.output_formats_path if non-empty, else assets/output-section-formats.md
• {scoringRulesPath} ← workflow.scoring_rules_path if non-empty, else references/scoring-rules.md
• {defaultThreshold} ← workflow.default_threshold if non-empty/non-null, else 80. CLI --threshold=<N> wins over per-pipeline defaults (from init.md §1b) which win over this scalar at the usage site in references/score.md.
• {onCompleteCommand} ← workflow.on_complete if non-empty, else empty string. When empty, the post-finalization hook in references/report.md is a no-op.

Stash all five as workflow-context variables. Stage files reference {testReportTemplatePath} / {outputFormatsPath} / {scoringRulesPath} / {defaultThreshold} / {onCompleteCommand} directly — no conditional at the usage site. Empty-string overrides cleanly fall through to the bundled default; non-empty values let orgs swap in house-style copies without forking the skill.

1. Load, read the full file, and then execute references/init.md to begin the workflow.