Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bestagentkits/agency-skills --skill commercial-forecastergit clone --depth 1 https://github.com/bestagentkits/agency-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-forecaster)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-forecaster"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/commercial-forecaster/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-forecaster"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/commercial-forecaster.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00194 | $0.02872 |
| Opus 5 | $0.00097 | $0.01436 |
| Sonnet 5 | $0.00039 | $0.00574 |
| Haiku 4.5 | $0.00019 | $0.00287 |
Grade A, and why
commercial-forecaster scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to commercial-forecaster — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
commercial-forecaster
Purpose
Help Commercial leaders answer three questions at the forecast moment:
- What's the commit / best-case / pipe-only number? (3-tier bookings forecast with disclosed assumptions)
- Which cohorts are leaking, and is the consolidated NRR hiding the leak? (per-cohort NRR/GRR projection over horizon)
- Which funnel stages are reliable, and which are statistical noise? (per-stage coefficient-of-variation confidence band)
The skill recommends three forecast numbers + an explicit assumption block. The CRO presents the number, the board sees the assumptions, the theatre dies.
When to use
- Building the quarterly bookings forecast for the board
- Preparing the QBR forecast where the CFO will ask "what's the commit, what's the best-case, what's the pipe-only"
- Projecting ARR for next 4-8 quarters using cohort retention data
- Suspecting a consolidated NRR number is hiding a leaky recent cohort
- Pipeline-coverage is shrinking and you need to know which stages are still trustworthy
- You're being asked for a "single number" and you need the structured answer that surfaces the assumption
Do not use for:
- Backward-looking financial close + reporting →
finance/financial-analysis - Strategic financial planning (multi-year, scenario, fundraise) →
c-level-advisor/cfo-advisor - "Should we hire a VP Sales?" / territory design / comp plan →
c-level-advisor/cro-advisor - Setting prices → sibling
pricing-strategist(projects revenue at prices already set) - Per-deal discount approval → sibling
deal-desk
Workflow
Step 1 — Intake pipeline + cohort + historical conversion data
Fill assets/forecast_intake_template.md (≈ 20 min). Captures: opportunity list with stage/amount/close-date/age/last-activity; historical stage-to-stage conversion across last 4Q and last 12Q; per-cohort ARR + per-quarter retention + expansion data; funnel stage names with 12-quarter conversion history.
Step 2 — Run 3-tier bookings forecast
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 218 B
- assets/forecast_intake_template.md 5.9 KB
- references/cohort_analysis_canon.md 6.4 KB
- references/forecast_anti_patterns.md 8.5 KB
- references/saas_forecasting_canon.md 7.0 KB
- scripts/bookings_forecaster.py 18 KB runs code
- scripts/cohort_arr_projector.py 12 KB runs code
- scripts/funnel_confidence_scorer.py 7.6 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 152 lines · 194 tokens per session scan A ad604e6d0e26
commercial-forecaster is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 194 tokens to every session and 2,872 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to commercial-forecaster, differing in 7 lines, and is treated as a copy.
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