agentleFS
calebnewtonusccalebnewtonusc/Chewbacca/skills/gtm-engineering/SKILL.md

gtm-engineering

Skill8 starsChanged 3 months agoMITView on GitHub

Build and evaluate GTM workflows in Clay: ICP, signals, list building, qualification, enrichment, sequencing, CRM routing, and outcome measurement. Use for operating or learning Clay and testing GTM automation reliability.

5 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 2

    Distinctive

    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
  1. Distinctive:

    Start with the business outcome, its denominator, maturity window, and budget.

    line 8
  2. Very specific:

    Read domains.md before choosing what to evaluate, and evaluation.md before claiming competence.

    line 28
  3. Distinctive:

    Update the relevant map or procedure only from observed behavior.

    line 32

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

GTM engineering

Start with the business outcome, its denominator, maturity window, and budget. Read existing client instructions and approved ICP before designing a workflow. Keep customer data and research corpora private.

Reuse before building

Use list-audit and list-gate for inherited contacts. Locate the installed official Clay plugin and read its command help and relevant skills before assuming capabilities. Probe account and workspace identity. Native workflow APIs, table reads, browser operations, and paid enrichments have different capabilities and costs. Use the browser-use skill for verified gaps. Search the private research corpus with gtme-library --corpus PATH search 'query'; retrieval is not evidence that the entire corpus was studied.

Maintain separate identity, execution, and evidence graphs. An account match does not prove current employment. A successful HTTP response does not prove the destination contains the intended rows. A source citation does not prove its claim is true.

Read the graph-engineering skill and its task-graphs reference for substantial multi-source work. Queue independent jobs with named owners, dependencies, expected artifacts, and acceptance checks. Use the runtime's actual concurrency limit; keep ready jobs queued when slots are full. Reserve a separate verifier context before merging implementation or research claims. Do not add dependencies between jobs that do not consume each other's results. Serialize shared-file writes and browser mutations.

Execute bounded tasks

Use gtme-graph --help to validate a frozen plan, initialize private state, select ready nodes, begin an attempt, and finish it with evidence. Each attempt reserves its maximum credits. Failed attempts also consume actual cost. Evidence must bind to the current run and attempt, be captured during that attempt, and include immutable source JSON with the required observations. Keep all attempt artifacts, including failures. This CLI enforces its own workflow state; it is not a global browser hook or an authenticated external witness.

Separate Actions, Data Credits, and external provider dollars. Never add unlike units. The graph budget tracks one explicitly chosen meter; account for other meters separately. Inspect auto-run and schedules before imports or edits. Start with a small fixture, then independently read back row count, stable IDs, mapped columns, and values. Retry only after inspecting whether the previous attempt partly succeeded.

Sending requires the user's actual authorization and approved campaign conditions. The graph tool intentionally never makes send nodes runnable. Drafting is not sending.

Learn and measure

Read domains.md before choosing what to evaluate, and evaluation.md before claiming competence. Use gtme-math order only under its stated fixed-cost independence assumptions. Use gtme-math funnel for matured binary outcomes and gtme-math evaluate for sealed qualification labels. None of these commands establishes causal business uplift.

After each substantial phase, compare the observed result with the baseline and falsifier, audit reusable capabilities, consider three alternatives, state the mathematical assumptions, and choose continue, revise, or stop. Record this with gtme-graph review when running a phased graph. Label novelty existing, adaptation, or unverified. Novelty is not a substitute for measured improvement.

Update the relevant map or procedure only from observed behavior. Distinguish documented, inspected, tested, and independently verified capabilities. Record coverage gaps and failures; do not graduate a domain because its tutorial was read.

Use clay-fixture-check to compare an exported CSV with a frozen synthetic fixture. It checks content, not export authenticity or workspace identity. Use gtme-learning evaluate for paired holdout results and regression preservation before proposing promotion. Its local declarations do not prove evaluator independence or that a test was sealed in advance. Obtain those receipts separately.

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.