Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/YALC-the-GTM-operating-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/YALC-the-GTM-operating-system/main/.claude/skills/predictleads-signals/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-systemWrote 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/othmane-khadri/yalc-the-gtm-operating-system/predictleads-signals)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/predictleads-signals"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/predictleads-signals/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/othmane-khadri/yalc-the-gtm-operating-system/predictleads-signals"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/predictleads-signals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, 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 MCP Rug Pull · line 23 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 26 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 29 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 32 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 33 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00074 | $0.00822 |
| Opus 5 | $0.00037 | $0.00411 |
| Sonnet 5 | $0.00015 | $0.00164 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
predictleads-signals scanned grade A with 1 finding 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 13d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Live PredictLeads quota: hit `/api_subscription` once via curl to see remaining credits. Or just run `signals:fetch` and the output prints cache hit / +N signals per type. How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PredictLeads Signals (single company)
Pulls and reads company-level intent signals from PredictLeads: job openings, financing events, technologies, news events, similar companies. Stored in local SQLite (company_signals table) with a 7-day TTL cache so repeat lookups within the week cost zero credits.
When to use
- Quick lookup before an outbound message: "what's happening at hubspot.com?"
- Adding signal context to a single lead during qualification
- Reading cached signals offline (no API call) via
signals:show - Sanity-checking a company's marketing maturity (tech stack, hiring pace)
Don't use when: enriching a list of >5 companies (use predictleads-lookalikes for discovery, or the bulk signals:enrich --result-set); building a campaign (use prospect-discovery-pipeline).
Quick reference
# Pull all 4 signal types for one company (1 credit per type = 4 credits)
npx tsx src/cli/index.ts signals:fetch --domain hubspot.com
# Restrict to specific types (saves credits)
npx tsx src/cli/index.ts signals:fetch --domain hubspot.com --types jobs,funding
# Force re-fetch even if cached within TTL
npx tsx src/cli/index.ts signals:fetch --domain hubspot.com --no-cache
# Read cached signals locally (no API call, free)
npx tsx src/cli/index.ts signals:show --domain hubspot.com --limit 20
npx tsx src/cli/index.ts signals:show --domain hubspot.com --type news
Cost
| Operation | Credits |
|---|---|
signals:fetch (4 types, default) |
4 |
signals:fetch --types jobs,funding |
2 |
signals:fetch re-run within 7 days |
0 (cache hit) |
signals:show |
0 (local read) |
Live PredictLeads quota: hit /api_subscription once via curl to see remaining credits. Or just run signals:fetch and the output prints cache hit / +N signals per type.
Signal types and aliases
jobs (job_opening), funding (financing), tech (technology), news, similar (similar_company)
Common pitfalls
- Domain format: pass the bare domain (
hubspot.com), nothttps://hubspot.comorwww.hubspot.com. The service tolerates either but URLs in payloads are cleaner. - News and tech rows look empty in
signals:show: payloads usesummary(news) and resolved relationships (tech) instead oftitle. The display already falls through tosummary. If you see blanks, check the raw payload viasqlite3 ~/.gtm-os/gtm-os.db "SELECT payload FROM company_signals WHERE domain='X' LIMIT 1". - Cache invalidation: 7 days is the default TTL. Pass
--no-cacheto force a refresh. Caching is per (domain, signal_type), so refreshing news doesn't re-pull jobs.
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.
- 13d ago First seen · 60 lines · 74 tokens per session scan A 3bbc788143ec
predictleads-signals is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 23d ago), licensed MIT. It adds 74 tokens to every session and 822 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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cn-check
Install and run the Continue CLI (cn) to execute AI agent checks on local code changes. Use when asked to "run checks", "lint with AI", "review my changes with cn", or set up Continue CI locally.
kn-spec
Use when creating a specification document for a feature (SDD workflow).
kn-handoff
Use when a feature crosses repository boundaries and one side must hand work to the other - generates a self-contained frontend-to-backend brief or backend-to-frontend API contract.
kn-flow
Use when orchestrating a full Knowns spec or task wave through planning, implementation, review, integration, and verification, optionally using sub-agents when scopes are parallel-safe.
kn-research
Use when you need to understand existing code, find patterns, search project knowledge, investigate current external facts, or explore a large codebase before implementation.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.