Content
56%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.
The body delivers genuinely non-obvious domain discipline (70/30 window blending, CoV-based stage confidence, leaky-cohort decomposition) in a clear five-step workflow, but it is held back by redundancy (repeated assumption-block rule, duplicated boundary sections), an inlined question library, and a broken dependency chain — every workflow step invokes scripts, references, or templates that are not present in the bundle.
Suggestions
Trim the assumption-block/"theatre" rule to a single statement in Assumptions and cross-reference it elsewhere, and merge "Do not use for" with "Distinct from" to remove the duplicated sibling-skill list.
Move the forcing-question library into a reference file (e.g., references/forcing_questions.md) and keep a one-line pointer plus the walk order in the body.
Ship the bundle files the workflow depends on (scripts/, assets/forecast_intake_template.md, references/) or specify the intake.json schema inline so each step is executable as bundled.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Most content is dense domain judgment Claude does not already know ("Last 4Q is weighted 70%, last 12Q is weighted 30%", CoV bands, 3x pipeline-coverage floor), but the "theatre"/assumption-block rule is repeated in Purpose, Step 2, Step 5, Assumptions, and question 7, and the "Do not use for" list fully duplicates "Distinct from" (the same five sibling skills restated). This is tighter than the padded-anchor 2 (no basic-concept explanations) but has more than the minor trimmable instances of the 4 anchor. | 3 / 5 |
Actionability | Guidance is concrete — exact CLI invocations ("scripts/bookings_forecaster.py --input intake.json --profile saas --output markdown") and precise numeric decision rules ("HIGH < 10%, MEDIUM 10-25%", "stage-age > 2x the median stage-duration") — but none of the referenced scripts, references, or the intake template exist in the bundle, and the intake.json schema is never specified. The pipeline cannot actually be executed as bundled, which is a missing-key-details gap rather than the minor gaps of the 4 anchor. | 3 / 5 |
Workflow Clarity | Five steps are clearly sequenced with named per-step outputs and decision rules (leaky-cohort flags, automatic downweighting of stalled opps, pipeline-coverage ratio surfaced by the tool). It misses the 5 anchor because there is no intake-data validation or error-recovery loop, and the forcing-question library introduces a second, partially redundant entry path ("After all 7 are answered, invoke bookings_forecaster.py..."); the destructive/batch cap at 3 does not apply since this is read-only analysis. | 4 / 5 |
Progressive Disclosure | Structure and signaling are good — "## Scripts" and "## References" sections list each file with a one-line description, one level deep — but none of the referenced files (three scripts, three references, one intake template) exist in the bundle, and the ~30-line forcing-question library is inlined content that belongs in a reference file. This sits between the 2 anchor (buried references/inlined separable content) and the 4 anchor (references mostly present and real). | 3 / 5 |
Total | 13 / 20 Passed |