zime-gtm-skills
AGENTS.md19 starsChanged 27 days agoMITView on GitHub
Guidelines for AI agents working in this repository. Open-source Agent Skills that audit sales call transcripts and CRM exports against per-GTM-motion rubrics. No Zime product coupling: every skill runs standalone, no API keys, no gating, no data leaves the user's machine. Skills install to .agents/skills/ (the cross-agent standard) and also work under .claude/skills/. SKILL.md stays under 500 lines. Move detail into references/. references/, scripts/, assets/, evals/ are one level deep, no nested reference chains. CI additionally runs the upstream spec's…
- Commits and pushes
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,439 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository72 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- account-plan-generatorSkill
- adoption-leaderboardSkill
- bantSkill
- call-prepSkill
- challengerSkill
- champion-trackerSkill
- channel-partner-engagementSkill
- churn-preventionSkill
- client-testimonial-finderSkill
- coaching-planSkill
- competitive-loss-digestSkill
- competitive-positioningSkill
- competitor-battlecardSkill
- crm-exportSkill
- customer-successSkill
- deal-desk-approval-briefSkill
- deal-highlightsSkill
- deal-risk-digestSkill
- deep-discoverySkill
- discount-pattern-digestSkill
- end-client-registrationSkill
- evaluation-pipeline-checkSkill
- executive-briefingSkill
- faintSkill
- first-call-rampupSkill
- follow-up-email-drafterSkill
- forecast-reviewSkill
- handover-to-customer-successSkill
- ideal-channel-partner-profileSkill
- improve-demoSkill
- loss-reviewSkill
- meddiccSkill
- meddpiccSkill
- meeting-to-qualifySkill
- multi-threadingSkill
- mutual-action-planSkill
- negotiation-closingSkill
- negotiation-pipeline-checkSkill
- new-business-registrationSkill
- next-step-commitmentSkill
- objection-pattern-digestSkill
- onboarding-journeySkill
- pain-finderSkill
- partner-business-reviewSkill
- partner-competition-landscapeSkill
- partner-decision-authoritySkill
- partner-pain-pointsSkill
- partner-potentialSkill
- partner-sentimentSkill
- persona-based-discoverySkill
- pilot-to-conversionSkill
- pipeline-reviewSkill
- poc-pilot-pipeline-checkSkill
- poc-successSkill
- prospect-pipeline-checkSkill
- qualify-pipeline-checkSkill
- qualify-to-pocSkill
- reference-case-study-drafterSkill
- renewal-prepSkill
- The first 60 shown.
The file
We split this AGENTS.md into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 9
No Zime product coupling: every skill runs standalone, no API keys, no gating, no data leaves the user's machine.
- Distinctive: line 78
Every automated check enforces a named rule, so a CI failure line points at what to fix, not just which script ran.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
AGENTS.md
Guidelines for AI agents working in this repository.
Repository overview
Open-source Agent Skills that
audit sales call transcripts and CRM exports against per-GTM-motion rubrics.
No Zime product coupling: every skill runs standalone, no API keys, no
gating, no data leaves the user's machine. Skills install to
.agents/skills/ (the cross-agent standard) and also work under
.claude/skills/.
- Name: zime-gtm-skills
- GitHub: zime-ai/zime-gtm-skills
- Maintained by: Zime
- License: MIT
Repository structure
zime-gtm-skills/
├── .claude-plugin/
│ ├── marketplace.json # /plugin marketplace add zime-ai/zime-gtm-skills
│ └── plugin.json
├── skills/
│ └── skill-name/
│ ├── SKILL.md # required
│ ├── references/ # optional, the rubric lives here
│ ├── assets/ # optional, synthetic sample transcript/CSV
│ └── evals/ # optional, evals.json, declarative for now
├── validate-skills.sh # local, zero-dep frontmatter/layout check
├── CONTRIBUTING.md
├── MAINTAINING.md # process + decisions, for picking this repo back up
├── ROADMAP.md # what's built, what's next
├── LICENSE
└── README.mdFrontmatter contract
| Field | Required | Constraints |
name | yes | 1–64 chars, lowercase [a-z0-9-], must equal the parent directory name |
description | yes | 1–1024 chars; state both what the skill does and when to use it |
license | no | defaults to MIT |
metadata | no | free-form; this repo uses zime:category, zime:dimension (stage/initiative/vertical-context), zime:input-modes, and (for stage skills) zime:stage |
SKILL.md stays under 500 lines. Move detail into references/.
references/, scripts/, assets/, evals/ are one level deep, no nested
reference chains.
Validate
./validate-skills.sh # local, seconds, zero deps
./scripts/check-docs-sync.sh # README count/table vs skills/, zero deps
python3 scripts/scan-content.py # content-level leak/injection scan, zero deps
scripts/skillspector-gate.sh all # static security scan (needs `skillspector` on PATH), or pass a base ref for changed skills onlyCI additionally runs the upstream spec's skills-ref validate on every PR,
pinned to a commit (see .github/workflows/validate.yml) since it isn't
published to PyPI.
tests/run-checks-tests.sh runs the above three against deliberately broken
fixtures (missing frontmatter, un-ignored private dirs, a leaked home path,
an injection pattern, ...) so a CI failure has been shown to catch
something, not only assumed to. Run it after touching any validator.
scripts/check-pr-diff-identity.py <base> <head> is different from the
three above: it's diff-scoped, not tree-scoped, and runs automatically
after scripts/pr-prep.sh opens a PR rather than before. See the
operator-identity rule above.
Rule registry
Every automated check enforces a named rule, so a CI failure line points at what to fix, not just which script ran.
| Rule ID | Enforced by |
frontmatter-contract | validate-skills.sh: name/description/dimension/line-count |
private-data-ignored | validate-skills.sh: evals/{transcripts,gt,cases,labels} stay gitignored |
readme-in-sync | scripts/check-docs-sync.sh |
roadmap-in-sync | scripts/check-docs-sync.sh: every skills/* dir has a - [x] line in ROADMAP.md and vice versa |
no-home-paths | scripts/scan-content.py: no /Users/<name> or C:\Users\<name> in tracked files |
no-injection | scripts/scan-content.py: no prompt-injection patterns in skills/*/SKILL.md or references/ |
no-hidden-unicode | scripts/scan-content.py: no zero-width/bidi-override/homoglyph chars |
no-client-names | scripts/scan-content.py: local-only, needs a gitignored .private/client-denylist.txt; skips (not a failure) when that file is absent, including in CI |
sample-required | validate-skills.sh: every skill with zime:dimension: stage or initiative must have assets/ (at least one file) and evals/evals.json; vertical-context skills are exempt, they're loaded by other skills rather than run directly |
operator-identity | scripts/check-pr-diff-identity.py: scans a PR's actual diff (not the whole tree) for the operator's own git config user.name/user.email, or a home-directory path; scripts/pr-prep.sh runs it after gh pr create, since the PR is already public by then, this can only warn, not block |
The two hard content rules
- Every finding in a transcript-mode audit cites a quote or timestamp. An uncited finding doesn't ship: this is the trust bar the whole repo is built on.
- Never expose anything that isn't already customer-visible in the Zime
product. Checklist titles and question text are customer-visible and
fine to draw on; internal scoring weights, thresholds, model
configuration, and customer/account data are not. See
MAINTAINING.mdfor the authoring process and how this gets enforced.
Building several skills at once? See MAINTAINING.md's "Building skills at
scale" for the worktree-per-skill and create-validate-iterate flow.
Evals
Each skill may carry evals/evals.json: declarative test cases (prompt +
sample file + expected expectations). They are not run in CI yet. See
EVALS.md for the full methodology: the three eval tiers, why format
compliance and insight recall are reported as two separate metrics rather
than one blended number, and where a human is required versus where nothing
is. Treat evals as the source of truth for "does this skill work,"
not the skills-ref/validate-skills.sh structural checks, which only
catch frontmatter and layout errors.
Two dimensions: stage, initiative
Skills cover deal stage and initiative as ordinary, flat skills
(zime:dimension: stage or initiative in frontmatter), never nested
under a skills/stage/ or skills/initiative/ directory, since that breaks
the install command above and both validators. A third axis,
vertical-context (a reference pack per industry any other skill can load
on request), was pulled off main before public launch pending
domain-expert review. See MAINTAINING.md's "Two dimensions" and
"Deferred work" sections, and the vertical-context branch.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

