launch-debrief skillA
launch-debrief is agent-read markdown (skill) from varunk130/ai-gtm-skill-library: Structured post-launch retrospective that produces quantified learnings and improvement playbooks. Use when: launch retrospective, post-launch review, what worked, launch debrief, post-mortem, lessons learned..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Launch Debrief (MIRROR Protocol) A structured post-launch retrospective engine that transforms raw launch data into quantified learnings, root-cause analyses, and improvement playbooks. MIRROR ensures every launch makes future launches better by extracting actionable insights from both successes and failures through systematic analysis rather than anecdotal recall. ## When to Use - Conducting a post-launch retrospective (ideally at T+30 and T+90) - Analyzing why a launch over- or underperformed expectations - Building an institutional knowledge base of launch learnings - Creating improvement playbooks for the next launch cycle - Presenting launch results to leadership with root-cause analysis - Comparing actual results against pre-launch projections - Identifying systemic issues across multiple launches ## What You'll Need **Critical inputs (ask if not provided):** - Launch name, date, and type (GA, beta, feature, expansion) - Pre-launch targets for all VITAL metrics (from launch-pulse) - Actual performance data for all tracked metrics - Launch readiness scores from gate reviews (from launch-command) - Budget allocation and actual spend (from budget-allocator) …
Read the whole file at its exact version.
How to install
mdr add varunk130/ai-gtm-skill-library/launch-debrief@git:20260516.4225f52mdr add varunk130/ai-gtm-skill-library/launch-debrief@sha256:f3a48732bb804b63Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_56y3i3b6l34aiqd4)
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Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (11097 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
varunk130/ai-gtm-skill-library · 6 stars · license MIT · pushed 2026-09-19 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_56y3i3b6l34aiqd4 GET https://markdownregistry.com/api/v1/resolve?ref=varunk130/ai-gtm-skill-library/launch-debrief GET https://markdownregistry.com/api/v1/blob/f3a48732bb804b638740f45b8279ed57947ca4eaffdbe2a159f813c4dc70bbcc
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