Content
88%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.
An exemplary short skill body: tight, non-patronizing prose; a numbered workflow with genuine validation checkpoints, a convergence criterion, and an explicit feedback loop; and concrete function-level guidance throughout. The only deductions are reliability-of-execution details — the placeholder kernel.py path and the absence of kernel.py in the bundle — which slightly weaken actionability and the verifiability of its progressive-disclosure structure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean throughout: it never explains what a manuscript or figure deck is, compresses setup into one exec line with a NameError troubleshooting note, and gives a 5-step workflow where every line is operational (e.g., "arc[] → the main-figure order. Anything not on it → supplement"). This matches the 5 anchor — it assumes Claude's competence and every token earns its place — with only negligible repetition of "you write the brief from the work", which does not rise to the 'minor instances' of the 4 anchor. | 5 / 5 |
Actionability | Mostly executable guidance: a concrete setup command `exec(open("paper-narrative/kernel.py").read())`, function calls with argument signatures (`paper_brief_prompt(abstract_text, figure_claims)`, `narrative_review_task(brief, deck_path, rules_path)`), and a minimal invocation example. It falls short of the 5 anchor because the kernel.py path is a placeholder ("path to this skill's kernel.py") and kernel.py is not present in the reviewed bundle, so the single code block is not verifiably copy-paste ready and the output JSON shapes are only available sight-unseen via schema functions. | 4 / 5 |
Workflow Clarity | The 5-step workflow is clearly sequenced with explicit checkpoints and a feedback loop: step 1 mandates re-reading the whole brief before proceeding, both JSON emissions must match schema functions, step 5 defines an explicit convergence criterion ("Converge when `would_send_for_review=="yes"` and `figure_moves` / `missing_panels` are empty") with a re-run loop, and setup errors are handled ("if one raises `NameError`, you haven't exec'd `kernel.py`"). This matches the 5 anchor; the skill is editorial rather than destructive/batch, so no validation cap applies. | 5 / 5 |
Progressive Disclosure | Structure is good for a short skill: clear sections (intro, Setup, When to load, Workflow, Minimal invocation) and a well-signaled single external dependency (kernel.py via the exec line, plus delegation to the separate `figure-composer` skill), one level deep. It is not a 5 because the deferred content — the schemas and prompt builders in kernel.py — cannot be navigated or verified from the SKILL.md alone (no bundle file is present), and the reference path is a placeholder rather than a resolvable link. | 4 / 5 |
Total | 18 / 20 Passed |