Content
82%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 lean, high-density instruction skill with a clearly sequenced workflow, concrete file artifacts and decision criteria, and well-signaled one-level references. The main gaps are that the referenced probe library and improvement-card template are not shipped in the bundle (with non-resolving path prefixes), and there is no fallback guidance for when the workspace data sources are missing.
Suggestions
Ship the four referenced files in the bundle and use skill-relative paths (references/loop-probes.md rather than skills/flow-driven/references/loop-probes.md), or inline a minimal probe checklist and improvement-card skeleton so the loop is executable from SKILL.md alone.
Add a fallback branch to step 2 for workspaces where board.md, flow-log.csv, or the improvement lane does not yet exist (e.g. 'no board yet — run only the definition-family probes and create the lane').
Include one compact worked example of a fired probe becoming an improvement card (signal, citation, benefit hypothesis, kill criteria) to make the capture step copy-paste concrete.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every section carries operational content — "Probes read data; they do not free-associate", "Three similar learnings count as a signal. A pass that fires nine probes produces a report nobody acts on" — with zero explanation of concepts Claude already knows and no padding across ~85 lines. Rationale one-liners like "edits made in passing are how operating models rot" justify rules in few tokens rather than over-explaining, so it sits at the 'lean and efficient' anchor rather than 4. | 5 / 5 |
Actionability | Concrete guidance throughout: named data sources ("board.md, flow-log.csv, reviews/loop-log.md, learnings/", "measures.md baselines"), counts ("Run 3–5 probes"), artifact paths ("improvements/<slug>/improvement.md", "reviews/YYYY-MM-DD-meta-loop.md") with enumerated card fields, and a right-sizing mapping ("A policy tweak needs a line and a decision. A rung promotion needs a shadow run"). It is not 5 because the core probe definitions and the bet-card template are deferred to referenced files (loop-probes.md, templates/improvement.md) that are not present in the bundle, so a reader cannot execute the primary loop from this file alone. | 4 / 5 |
Workflow Clarity | The eight steps are clearly ordered with data gathering before probing, per-probe decision criteria ("signal present? Cite the rows, items, or dates. No signal? One 'checked, quiet' line"), and a Quality Gates checklist verifying the end state ("Zero direct edits to workflow.md or step contracts in this invocation"). It is not 5 because there is no error-recovery feedback loop — e.g. what to do when board.md, flow-log.csv, or the improvement lane does not exist yet — leaving a gap between 'gather data' and 'run probes'. | 4 / 5 |
Progressive Disclosure | Good structure: a compact overview body with a dedicated References section giving each file a one-line description ("loop-probes.md — the four probe families", "evolution-path.md — stages, human roles, the platform play"), all one level deep. It is not 5 because none of the four referenced files exist in the bundle (no references/ or templates/ directories) and the paths carry a 'skills/flow-driven/' prefix that will not resolve relative to SKILL.md, so step 1's "Load the probe library" points nowhere verifiable — more than a trivial organization gap, though the signaling itself is clear enough to sit above anchor 3. | 4 / 5 |
Total | 17 / 20 Passed |