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 shawnla90/gtm-coding-agent --skill moltsets-reachabilitygit clone --depth 1 https://github.com/shawnla90/gtm-coding-agentWrote 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/shawnla90/gtm-coding-agent/moltsets-reachability)<a href="https://agentmods.dev/skills/shawnla90/gtm-coding-agent/moltsets-reachability"><img src="https://agentmods.dev/badge/skills/shawnla90/gtm-coding-agent/moltsets-reachability/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/shawnla90/gtm-coding-agent/moltsets-reachability"><img src="https://agentmods.dev/badge/skills/shawnla90/gtm-coding-agent/moltsets-reachability.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 | $0.00282 | $0.02354 |
| Opus 5.5 | $0.00113 | $0.00942 |
| Sonnet 5.5 | $0.00056 | $0.00471 |
| Haiku 4.5 | $0.00028 | $0.00235 |
Grade A, and why
moltsets-reachability 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 1mo 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
moltsets-reachability
A bad email grade is a routing decision, not a dead contact.
Relevance, timing, reachability. Title scoring covers relevance. The Apollo employment check covers timing. The Moltsets grade covers reachability, and the route column is what you do when the grade says no. Wraps starters/moltsets-reachability/: the scripts call the APIs and build the sheet; the agent reads the dashboard back to the user and decides what to send. Read FACTCHECK.md before writing a single sentence about what a grade means or what a call costs.
Inputs
- A contact CSV: the short schema (
first_name,last_name,title,company,domain,email,linkedin_url) or a raw Apollo people export with its original headers MOLTSETS_API_KEY(env,.env, orSECRETS_DBvault).APOLLO_API_KEYoptional, powers--employment apollo|both~/.config/gspread/token.jsonfromsetup_oauth.py- Optional:
--exclude <file>of emails or LinkedIn URLs that must never be graded (people already in your pipeline) - Optional, no flag: a verifier verdict column on the CSV (
zb_status,zerobounce_status,verifier_status,verification_status; pluspool,mx_provider). Detected by alias, normalized tovalid | catch-all | unknown | invalid | do_not_mail | abuse. Turns on delta classes and the two comparison tabs. - Optional: a CSV of rows already graded elsewhere for
import_graded.py(grade, molt_email, still_at_company, zb_status, tier, route, delta_class by alias)
How to run
cd starters/moltsets-reachability
python3 budget.py # free: pools, phone tokens, endpoint count. Always first.
python3 init_db.py my_list.csv --exclude pipeline.txt
python3 grade.py --limit 20 --dry-run # shows what would run, spends nothing
python3 grade.py --second-pass # the waterfall (Moltsets employment check)
python3 grade.py --employment both --second-pass # add Apollo people/match and an agree column
python3 score.py
python3 build_sheet.py # prints the sheet URL; emails obfuscated
python3 build_sheet.py --summary-only --share anyone_reader # Dashboard + Verifier vs Moltsets, no rows: safe to link
REACHABILITY_DB=data/other.db python3 import_graded.py results.csv # rows graded elsewhere, own database, no API calls
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.
- 1mo ago First seen · 113 lines · 0 tokens per session scan A 81f0d93f7729
moltsets-reachability is a skill published in the GitHub repository shawnla90/gtm-coding-agent (156 stars, last pushed 1mo ago), licensed MIT. It adds 282 tokens to every session and 2,354 once invoked, about $0.0011 per session on Opus 5.5. 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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