Content
70%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-engineered workflow with excellent sequencing, validation gates, and safety rails (log-driven evidence requirements, deletion safeguards, review + approval gates). Its weaknesses are size and placement: verbose essays, an inlined event schema, and a full embedded reviewer prompt make the file monolithic when one-level-deep reference files would serve better, and a few code snippets are not safely copy-pasteable as written.
Suggestions
Move the Event Schema Reference (JSONL record shapes) and the full Step 4 reviewer prompt template into a references/ file (e.g. references/event-schema.md and references/reviewer-prompt.md), keeping a one-line pointer in the main body — this addresses both the conciseness and progressive-disclosure gaps.
Tighten the model-delta and trigger-rate analysis sections to their operative rules (deletion requires target-specific evidence; never-delete list; measure-only trigger rates) and trim the Step 4 scope-limits block to its distinctive rules, cutting the rhetorical framing.
Make the code snippets safely copy-pasteable: parameterize the ledger writer's sample fields (read bottleneck/evidence from variables) and fix the Step 0 grep-count pattern (grep -c prints 0 on no-match, so '|| echo 0' double-prints and breaks the integer comparison).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly ARIS-specific and actionable, but several sections over-explain: the opening reviewer-slot blockquote, the multi-paragraph "model-delta analysis" and "trigger-rate analysis" essays with rhetorical padding ("A harness that only ever grows is a harness nobody is re-reading"), and the embedded 40-line scope-limits block in Step 4. Not score 4 because these verbose passages are recurrent rather than minor; not score 2 because the bulk is concrete workflow content Claude does not already know. | 3 / 5 |
Actionability | Step 0's bash availability check and Step 1.5's python ledger writer are copy-paste-ready, and the diff, ranked-table, and report templates give concrete output shapes. Not score 5 because the ledger snippet hardcodes sample values ("cycle": 3, "bottleneck": "verification quality") that would silently write wrong data if pasted as-is, the Step 0 grep-count fallback pattern mishandles the zero-match case, and several helper paths (tools/capture_filter.py, trigger_eval.py, save_trace.sh) are named without resolution instructions beyond a chain pointer. | 4 / 5 |
Workflow Clarity | Steps 0-6 are clearly sequenced with explicit validation checkpoints throughout: the Step 0 data-availability gate exits on insufficient data, Step 3 runs an anti-self-poisoning screen, Step 4 enforces a fresh adversarial review with a numeric score threshold ("If score < 7, explain what additional evidence would be needed"), and Step 6 gates application on user approval with mandatory backup and logging. This matches the anchor's clear sequence, explicit validation, and error-recovery feedback loops. | 5 / 5 |
Progressive Disclosure | Section headers are clear and external references are signaled with proper markdown links (../shared-references/capture-antipatterns.md, output-manifest.md, review-tracing.md), but the ~340-line body inlines material that belongs in reference files: the full Event Schema Reference with JSONL examples, the complete Step 4 reviewer prompt, and the Triggering/acknowledgements prose. The bundle contains no references/, scripts/, or assets/ directories, so every linked path (../shared-references/*, tools/meta_opt/trigger_eval.py) points outside the bundle. Not score 4 because content that should be split out is inline and the skill functions as a monolithic document rather than an overview; not score 2 because structure and signaling of what exists are good. | 3 / 5 |
Total | 15 / 20 Passed |