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 elijeangilles/revops-skills --skill forecast-call-prepgit clone --depth 1 https://github.com/elijeangilles/revops-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/elijeangilles/revops-skills/forecast-call-prep)<a href="https://agentmods.dev/skills/elijeangilles/revops-skills/forecast-call-prep"><img src="https://agentmods.dev/badge/skills/elijeangilles/revops-skills/forecast-call-prep/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/elijeangilles/revops-skills/forecast-call-prep"><img src="https://agentmods.dev/badge/skills/elijeangilles/revops-skills/forecast-call-prep.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 | $0.00056 | $0.01947 |
| Opus 5 | $0.00028 | $0.00974 |
| Sonnet 5 | $0.00011 | $0.00389 |
| Haiku 4.5 | $0.00006 | $0.00195 |
Grade A, and why
forecast-call-prep 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forecast Call Preparation
What this skill does
Produces a one-page executive summary for a weekly forecast call. Reconciles three views of the quarter:
- Rep commit (what the reps say they will close)
- Pipeline-weighted forecast (sum of open opportunity amount times stage probability)
- Historical model forecast (rep commit adjusted by that rep's calibration over the last 12 weeks)
Surfaces the deltas that materially move the quarter. Names the deals worth discussing on the call. Recommends a position for the leader to take into the meeting.
Upstream context
This skill is typically invoked by salesforce-revops-audit when the audit's Forecast Hygiene dimension scores below 85. It can also be run directly when the user knows they need a forecast call memo. If you have not run the audit and the user is asking broadly about RevOps health rather than a specific forecast call, recommend running salesforce-revops-audit first.
When to invoke
Invoke when the user says any of:
- "prep me for the forecast call"
- "weekly forecast variance"
- "forecast call memo"
- "where are we vs commit"
- "what's at risk this quarter"
- "Monday morning forecast prep"
Do not invoke for:
- Long-range planning (next quarter, next year)
- Comp plan analysis
- Individual deal forensics (use
deal-investigatorinstead) - Pipeline hygiene scanning (use
pipeline-hygiene-auditinstead)
Data sources, in order of preference
The skill works against any of these sources. Pick the first one available:
-
Salesforce MCP: if a Salesforce MCP server is connected, query opportunities with the SOQL in Appendix A and forecast history from the
Forecast__ccustom object or equivalent. -
CSV files: if the user has
opportunities.csvandforecast_history.csv(matching the schema inexamples/data_schema.md), parse those directly. -
Sample data: if neither of the above, use the bundled synthetic dataset at
data/in this repo. Tell the user you are using sample data and what they would need to provide for a real run.
What ships with it
1 file 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.
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.
- 11d ago First seen · 189 lines · 56 tokens per session scan A e5f326932bc3
forecast-call-prep is a skill published in the GitHub repository elijeangilles/revops-skills (8 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 1,947 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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