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 First-Touch-Inc/firsttouch-agent-skill-packs --skill workspace-auditgit clone --depth 1 https://github.com/First-Touch-Inc/firsttouch-agent-skill-packsWrote 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/first-touch-inc/firsttouch-agent-skill-packs/workspace-audit)<a href="https://agentmods.dev/skills/first-touch-inc/firsttouch-agent-skill-packs/workspace-audit"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/workspace-audit/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/first-touch-inc/firsttouch-agent-skill-packs/workspace-audit"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/workspace-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00076 | $0.01925 |
| Opus 5 | $0.00038 | $0.00962 |
| Sonnet 5 | $0.00015 | $0.00385 |
| Haiku 4.5 | $0.00008 | $0.00193 |
Grade A, and why
workspace-audit 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workspace Audit
Outcome: An optional pre-flight check for teams that want to verify their setup before scaling - catch configuration gaps before they waste sends. Produce a readiness scorecard so a customer knows exactly what to fix before going live.
First-run onboarding gate
Before running this skill for the first time in a workspace, load ../../references/onboarding.md and complete the onboarding questions. Do not proceed until you know: LinkedIn account type (free/basic = no connection notes; recommend 10 connection requests/day and never exceed the FirstTouch max of 20/day; Sales Navigator/Premium = connection notes available; recommend 20 connection requests/day and never exceed the FirstTouch max of 30/day), HubSpot access (MCP, service key/private app token, HubSpot list only, or none), and which play the user wants to run. Recommend high-intent plays before outbound to keep the LinkedIn account healthy. If HubSpot is unavailable, do not run HubSpot-specific steps unless the user provides a HubSpot list FirstTouch can access.
When to use
- New customer onboarding ("are we ready to launch?")
- Before a big campaign push
- Outreach is underperforming and you suspect configuration, not copy
- Quarterly health check
Step-by-step
Every check below is one of two kinds, and the scorecard must keep them separate so a "ready" score can never hide unverified areas:
- [AUTO] - verifiable through the connected MCPs. Mark ✅/❌ from live data only.
- [MANUAL] - needs the user or the FirstTouch/HubSpot dashboard. Mark
manual check required; never guess, and never count an unchecked item toward the readiness score.
1. Check MCP connectivity [AUTO]
- FirstTouch MCP reachable + returns campaign/seat data? ✅/❌
- HubSpot MCP reachable + returns contacts/owners? ✅/❌ (if a play needs it)
- FirstTouch enrichment available and credits understood for AI SDR? ✅/❌/n/a; external Clay/Surfe enrichment MCP is optional, not required
2. LinkedIn account health (FirstTouch) [AUTO + MANUAL]
- Seat connected and authenticated? ✅/❌
- Current usage vs. daily limits (connection requests, messages, views) when available from FirstTouch
- Seat status in FirstTouch Social settings: Available = good; cooldown = hit its daily limit (normal, plan volume accordingly); Action required / Disconnected / Restricted = resolve before that seat sends
- SSI / account age / warmup status - manual/dashboard check unless FirstTouch exposes it directly
- If FirstTouch cannot return a metric, ask the user to check the FirstTouch dashboard and mark that metric
manual check required
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 · 123 lines · 76 tokens per session scan A 446bb11f05f2
workspace-audit is a skill published in the GitHub repository First-Touch-Inc/firsttouch-agent-skill-packs (5 stars, last pushed 2mo ago), licensed MIT. It adds 76 tokens to every session and 1,925 once invoked, about $0.0004 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 2026-08-31.
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