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 swan-gtm/gtm-skills --skill build-listgit clone --depth 1 https://github.com/swan-gtm/gtm-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/swan-gtm/gtm-skills/build-list)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/build-list"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/build-list/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/swan-gtm/gtm-skills/build-list"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/build-list.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.03175 |
| Opus 5 | $0.00023 | $0.01588 |
| Sonnet 5 | $0.00009 | $0.00635 |
| Haiku 4.5 | $0.00005 | $0.00317 |
Grade A, and why
build-list 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 9d 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
Setup state. Not yet configured for this org. Load the Readme sub-page once to capture the org's default column plan, sourcing tier order, and activation defaults. (Rewrite this paragraph via swan-update-skill after setup so future runs read the current config and skip re-checking.)
The mental model — column ladder
Every list build is a table. Each column has four properties:
- Input — which earlier columns it reads.
- Cost tier — free filter / free elimination / cheap enrichment / AI research / paid contact data.
- Run-when condition — which upstream Boolean gates it (almost always
icp_pass). - Fallback — what to write when it can't resolve.
You never "search and figure out what to do with the results." You write the column plan, show it to the user, then run it. Cheap filters kill the most rows; only survivors reach the expensive columns.
Step 0 — Lock the brief, push back on fuzz
Before any tool call, restate the brief as WHO + WHAT + WHY + SIZE:
- WHO — which ICP segment + which persona(s). If the org has multiple segments and the user hasn't picked one, ask.
- WHAT — which constraints are hard (must) vs soft (nice-to-have).
- WHY — which motion (cold blast, ABM, signal-trigger, event follow-up, competitor displacement).
- SIZE — target row count.
Push back hard if the brief contradicts the org's saved ICP segments. Don't silently obey "build me a list of dentists in Ohio" when the org sells observability to engineering teams — call it out and ask whether this is a real off-ICP experiment or a misfire.
If the brief is "lots of SaaS companies that might want X" — that's not a brief. Ask which sub-segment, what size band, what signal.
Step 1 — Size the audience first
Before any full pull, always run a sizing call with size: 1 to learn the audience volume cheaply. Use swan-fetch-businesses with the candidate filter set and size: 1; read the total field.
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.
- 9d ago First seen · 248 lines · 46 tokens per session scan A a7a08eb70609
build-list is a skill published in the GitHub repository swan-gtm/gtm-skills (150 stars, last pushed 2d ago), licensed MIT. It adds 46 tokens to every session and 3,175 once invoked, about $0.0002 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 2026-09-03.
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