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 tigerless-labs/auto-gtm --skill topic-scoutgit clone --depth 1 https://github.com/tigerless-labs/auto-gtmWrote 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/tigerless-labs/auto-gtm/topic-scout)<a href="https://agentmods.dev/skills/tigerless-labs/auto-gtm/topic-scout"><img src="https://agentmods.dev/badge/skills/tigerless-labs/auto-gtm/topic-scout/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/tigerless-labs/auto-gtm/topic-scout"><img src="https://agentmods.dev/badge/skills/tigerless-labs/auto-gtm/topic-scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 102 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00136 | $0.02055 |
| Opus 5 | $0.00068 | $0.01027 |
| Sonnet 5 | $0.00027 | $0.00411 |
| Haiku 4.5 | $0.00014 | $0.00205 |
Grade A, and why
topic-scout 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
topic-scout — one topic report, two parts
Turn a repo + today's internet into a short topic report. Ask the user nothing — and decide for them: the few product topics most worth posting, plus recent hotspots in full, all in one md. Both parts always run. Drafting the post/comment is downstream (x-content-generator, reddit-post-drafter, the comment skills).
Storage: read/refresh ~/Documents/auto-gtm/ — see ../gtm-shared/references/storage.md. The promoted product/repo + highlights come from there (or the trigger).
Say what's coming — first line, before any fetch
The report takes a while because it reads several sources. Set the expectation instead of asking a question: emit this line before the first fetch, then run both parts without stopping.
Building your topic report — A: launch + update topics from your highlights and merged PRs; B: builder digest (X, blogs, podcasts) + recent hotspots. Reading several sources, so this takes a moment.
Announce once. Never turn it into a question, a menu, or a chance to pick one part.
Part a — product topics (what you have to say)
Ask nothing, run both sources every time, and know the quota before you start: launch_topics_max = 2, update_topics_max = 2 (each type capped on its own; neither borrows the other's slots). Read all the highlights and all the recent merged PRs first — judgment needs the whole field — then write only the ones that make the cut. Never draft the full list and trim it afterwards: that yields the first two of nine instead of a topic you actually composed. What doesn't make the cut doesn't appear — not as a list, not as a footnote. The user wants a decision, not a menu.
What makes the cut — value to the developer audience: will a reader change their mind or do something differently because of this? Not "is it true", not "is it the newest", not "have I covered everything". Coverage is not the standard.
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 · 109 lines · 136 tokens per session scan A cff77a53361a
topic-scout is a skill published in the GitHub repository tigerless-labs/auto-gtm (344 stars, last pushed 7d ago), licensed MIT. It adds 136 tokens to every session and 2,055 once invoked, about $0.0007 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 2026-08-30.
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