Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/gtm-engineer-playbook. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/gtm-engineer-playbook/main/.claude/skills/gtm-playbook/weekly-gtm-report/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/gtm-engineer-playbookWrote 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/othmane-khadri/gtm-engineer-playbook/weekly-gtm-report)<a href="https://agentmods.dev/skills/othmane-khadri/gtm-engineer-playbook/weekly-gtm-report"><img src="https://agentmods.dev/badge/skills/othmane-khadri/gtm-engineer-playbook/weekly-gtm-report/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/othmane-khadri/gtm-engineer-playbook/weekly-gtm-report"><img src="https://agentmods.dev/badge/skills/othmane-khadri/gtm-engineer-playbook/weekly-gtm-report.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 | $0.00058 | $0.03257 |
| Opus 5.5 | $0.00023 | $0.01303 |
| Sonnet 5.5 | $0.00012 | $0.00651 |
| Haiku 4.5 | $0.00006 | $0.00326 |
Grade A, and why
weekly-gtm-report 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 1mo 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly GTM Report
Generate a structured weekly GTM performance report by reading data from the local docs/ directory and optional CRM exports. Produces an executive-ready summary with metrics, highlights, week-over-week trends, and recommended actions.
Tools Used
- Read — load pipeline data, signal reports, account briefs, sequence configs, battlecards, meeting prep notes, CRM CSV exports, and previous reports
- Write — save the weekly report and update the reports index
- Glob — discover available data files across
docs/subdirectories - Bash — date calculations (week number, date ranges)
Methodology
Follow these steps in order. Do not skip steps. Do not fabricate metrics. If data is missing for a section, include the section with a "No data available" note and a suggestion for how to populate it.
Step 1: Data Collection
Ask the user:
What week is this report for? (default: current week)
Use Bash to compute the ISO week number and Monday-to-Friday date range for the target week.
Then scan the docs/ directory for available data sources. Run these searches:
Glob: docs/pipeline/scored-leads.md
Glob: docs/signals/*.md
Glob: docs/accounts/*.md
Glob: docs/sequences/*.md
Glob: docs/battlecards/*.md
Glob: docs/meeting-prep/*.md
Glob: docs/reports/week-*.md
Also ask the user:
Do you have a CRM export CSV for this week? If so, provide the file path.
Read every file that exists. For each data source found, summarize what was loaded (file count and date range of contents). For each data source NOT found, note it as unavailable. Present the summary to the user before proceeding:
Data loaded:
- Pipeline: scored-leads.md (12 leads, last updated 2026-03-07)
- Signals: 4 signal reports found
- Sequences: not found
- Battlecards: 3 battlecards found
- Meeting prep: not found
- Previous reports: 2 found (latest: week-2026-W10)
I'll build the report from what's available. Missing sections will note what data is needed.
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.
- 1mo ago First seen · 296 lines · 58 tokens per session scan A 7e8bda20ea29
weekly-gtm-report is a skill published in the GitHub repository Othmane-Khadri/gtm-engineer-playbook (59 stars, last pushed 6mo ago), licensed MIT. It adds 58 tokens to every session and 3,257 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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