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 agentmods add skills/techwolf-ai/ai-first-toolkit/setupnpx skills add techwolf-ai/ai-first-toolkit --skill setupgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWhat 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 | $0.00072 | $0.00958 |
| Opus 5 | $0.00036 | $0.00479 |
| Sonnet 5 | $0.00014 | $0.00192 |
| Haiku 4.5 | $0.00007 | $0.00096 |
Grade A, and why
setup 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 2d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup
Principle: "You are responsible." This skill discovers and proposes. The manager validates and decides what's accurate.
Interactive onboarding that builds the foundation every other skill relies on. Crawls connected sources, extracts context, and validates with the manager before saving.
If any MCP connector is unavailable, follow the connector unavailability protocol in references/operating-principles.md.
Prerequisites
Ensure these MCP connectors are available:
- Slack: team channels, messages, terminology
- Notion: performance docs, goals, team pages
- Google Drive: 1:1 docs, meeting notes, strategy docs
- Gmail: communication patterns
- Google Calendar: recurring meetings, team rhythms
If any connector is missing, note it and proceed with what's available. Flag gaps at the end.
Instructions
Run phases sequentially. Each phase discovers, validates with the manager, then persists. Read references/discovery-phases.md for detailed instructions per phase.
Phase 1: Team Discovery
Identify the manager (name, role, teams), crawl sources for direct reports, validate the team list, discover internal terminology, find development goals and performance data, map ways of working, and identify customer/project context if applicable.
Persist: manager-context/manager-profile.md, manager-context/team/[name].md per report, manager-context/terminology.md, manager-context/sources.md
Phase 2: Performance & Management Frameworks
Discover how the org evaluates performance and managers. Search for existing framework docs, then walk the manager through defining their dimensions, rating scale, promotion readiness labels, review cadence, goal cadence, and management competencies. See references/performance-framework.md and references/management-framework.md for how skills use these frameworks.
Persist: manager-context/performance-framework.md, manager-context/management-framework.md
Phase 3: Organizational Values
Ask if the org has defined values. If yes, search for documentation, extract value names and behaviours, ask what signals to look for per value. If no, skip the values lens.
What ships with it
6 files 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.
- 2d ago First seen · 91 lines · 72 tokens per session scan A 7435f8278874
setup is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (96 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 958 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 2026-08-30.
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