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commercial-forecaster

Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number — especially when the CRO needs to walk the board through funnel math + cohort ARR + per-stage conversion assumptions without the theatre of a single undefended number. Decomposes pipeline into commit, best-case, and pipe-only tiers; projects cohort-level NRR/GRR to surface leaky cohorts before they show up in the consolidated number; scores per-stage funnel confidence so soft-floor stages get treated differently from high-confidence ones. Every output explicitly names the conversion rate used, the data window, and the weighting choice. For Head of Commercial, RevOps, VP Sales, and CRO at quarterly forecast or board prep. NOT financial close (see finance/financial-analysis). NOT strategic CRO hiring/territory (see c-level-advisor/cro-advisor). NOT pricing (see sibling pricing-strategist).

72

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

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The canonical home for this skill is commercial-forecaster in alirezarezvani/claude-skills

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, highly actionable body with concrete CLI commands, explicit thresholds, a clear 5-step workflow, and well-organized doctrine sections. The main weaknesses are mild cross-section repetition, the absence of an explicit validate→retry loop, and referenced bundle files that do not exist in the bundle.

Suggestions

State the "assumption block is non-optional" hard rule and the 70/30 blend once in Assumptions and reference it from Workflow, Anti-patterns, and the forcing-question library to remove the repetition.

Add an explicit validate→fix→retry loop to the workflow: if the assumption block is rejected, a leaky cohort is flagged, or pipeline-coverage falls below 3x, revise the intake and re-run the scripts before assembling the deck.

Ship the referenced bundle files (scripts/bookings_forecaster.py, cohort_arr_projector.py, funnel_confidence_scorer.py; references/saas_forecasting_canon.md, cohort_analysis_canon.md, forecast_anti_patterns.md; assets/forecast_intake_template.md) so the one-level-deep references resolve instead of dead-ending.

DimensionReasoningScore

Conciseness

Mostly efficient and domain-specific with no basic-concept over-explanation, but the "theatre" framing and the 70/30 blend are restated across Workflow, Assumptions, Anti-patterns, and the forcing-question library — minor instances that could be trimmed. Not a 5 because the repetition is noticeable; not a 3 because each restatement sits in a distinct functional context and assumes Claude's competence.

4 / 5

Actionability

Fully executable copy-paste-ready commands ("scripts/bookings_forecaster.py --input intake.json --profile saas --output markdown") with specific flags, plus concrete thresholds (CoV HIGH <10% / VERY LOW >50%, 3x coverage floor, 70/30 weighting) and "--help and --sample work on all three".

5 / 5

Workflow Clarity

Clear 5-step sequence (Intake → 3-tier forecast → cohort projection → funnel confidence → assemble deck) with explicit checkpoints ("The assumption block is non-optional", leaky-cohort callout, pipeline-coverage check) and a gated grill sequence. Not a 5 because a true validate→fix→retry recovery loop is not articulated for the main workflow; the scripts produce one-shot markdown rather than re-run-until-valid.

4 / 5

Progressive Disclosure

Good body structure — clear overview, well-signaled one-level-deep references (Scripts/References sections each describe their file's contents), easy navigation. Not a 5 because the referenced bundle files (scripts/*.py, references/*.md, assets/forecast_intake_template.md) are not actually present in the bundle, so the one-level-deep references currently dead-end.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete multi-action capability list, natural domain trigger terms, explicit what+when guidance, and explicit conflict boundaries routing to sibling skills. Third-person voice is maintained throughout with no first/second-person drift.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Decomposes pipeline into commit, best-case, and pipe-only tiers", "projects cohort-level NRR/GRR", "scores per-stage funnel confidence", "names the conversion rate used, the data window, and the weighting choice" — with comprehensive coverage of the skill's outputs.

5 / 5

Completeness

Explicitly answers both what (decompose/project/score) and when ("Use when building a quarterly bookings forecast...") with concrete trigger phrases and a named role context.

5 / 5

Trigger Term Quality

Uses natural terms a CRO/RevOps would actually say — "quarterly bookings forecast", "ARR projection", "pipeline forecast", "NRR projection", "commit/best-case/pipe-only board number" — with synonym coverage (forecast/projection).

5 / 5

Distinctiveness Conflict Risk

Clear niche with explicit boundary clauses — "NOT financial close (see finance/financial-analysis)", "NOT strategic CRO hiring/territory", "NOT pricing (see sibling pricing-strategist)" — minimizing wrong-skill triggering.

5 / 5

Total

20

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 10 missing

Warning

Total

14

/

16

Passed

Repository
alirezarezvani/claude-skills
Reviewed

Table of Contents

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