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 well-built operational skill body: copy-paste executable commands, a concrete five-step workflow with named scripts and industry profiles, explicit assumptions/anti-patterns, and a genuine one-level-deep bundle whose referenced files all exist. The main improvements are trimming repetition around the forcing-question library (or moving it to a reference file) and adding an explicit input-validation/error-recovery note to the workflow.
Suggestions
Move the forcing-question library (with its per-question canon citations) into a references/ file, keeping only the seven question stems and the lock order in SKILL.md — this trims conciseness and tightens the overview at the same time.
Add one validation step to the workflow, e.g. after intake: 'Confirm all required fields in assets/deal_intake_template.md are present before scoring; if not, return to the AE' — this gives the 5-step sequence an explicit feedback loop.
Deduplicate the uncapped-indemnity / critical-signal override explanation, which currently appears in the sample note, question 4, and the Anti-patterns section.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is largely efficient — operational facts Claude could not know (script names, flags, industry profiles, scoring weights, sibling-skill boundaries) with almost no generic-concept padding. Minor over-explanation could be trimmed: the forcing-question library repeats rationale already stated in Assumptions and Anti-patterns (e.g. the uncapped-indemnity override appears in both the sample note and question 4). This fits the 4 anchor (efficient, minor trimmable instances) rather than the 5 anchor (every token earns its place) and is well above the 3 anchor (unnecessary explanation). | 4 / 5 |
Actionability | Guidance is fully executable: the Quick examples block gives copy-paste commands (`python3 scripts/deal_scorer.py --input my_deal.json --profile enterprise-software`, `--sample`, `--output {human,json}`), the Scripts table maps each tool to its profiles, and the workflow specifies the exact input files and how to override thresholds (`policy_thresholds` in the input JSON). This matches the 5 anchor (copy-paste ready commands covering common cases); the 4 anchor would require minor gaps in the runnable examples, which are absent. | 5 / 5 |
Workflow Clarity | The 5-step workflow (intake → score → route → redline → assemble) is clearly sequenced, each step names its script and expected output, and the ordering rule in the forcing-question section ("Lock 1-4 before opening 5-7") plus the critical-signal override note provide decision checkpoints. It falls short of the 5 anchor because there is no explicit validation/feedback loop — e.g. what to do when intake JSON is incomplete or a script errors — though the deterministic stdlib scripts with --help and --sample soften that gap. It is above the 3 anchor since checkpoints (critical-signal override, explicit modifiers, assemble-only-after-scan) are present. | 4 / 5 |
Progressive Disclosure | Structure is good and matches the actual bundle: all three references (deal_desk_canon.md, discount_economics.md, contract_landmines.md), all three scripts, and the assets/deal_intake_template.md are real files, clearly signaled one level deep from the References/Scripts/Workflow sections. It stops short of the 5 anchor because substantial content is inlined in SKILL.md that could live in a reference file — notably the ~30-line forcing-question library with per-question canon citations — making the overview less lean than the 5-anchor example. | 4 / 5 |
Total | 17 / 20 Passed |