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 techwolf-ai/ai-first-toolkit --skill one-on-one-prepgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWrote 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/techwolf-ai/ai-first-toolkit/one-on-one-prep)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/one-on-one-prep"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/one-on-one-prep/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/techwolf-ai/ai-first-toolkit/one-on-one-prep"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/one-on-one-prep.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 | $0.00067 | $0.01921 |
| Opus 5.5 | $0.00027 | $0.00768 |
| Sonnet 5.5 | $0.00013 | $0.00384 |
| Haiku 4.5 | $0.00007 | $0.00192 |
Grade A, and why
one-on-one-prep 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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1:1 Prep
Great 1:1s live at the intersection of performance and care. Development keeps growth alive. Wellbeing makes sure the person behind the work is seen. Both matter every time.
Deep-dive preparation for 1:1 meetings with a specific direct report, anchored in the org's performance framework (from manager-context/performance-framework.md) and organizational values.
When to Use
- Before any 1:1 meeting with a direct report
- When the manager says "prep my 1:1 with [name]", "what should I discuss with [name]"
- Can be invoked with just a name, the skill finds the relevant context
Instructions
If any MCP connector is unavailable, follow the connector unavailability protocol in references/operating-principles.md.
1. Identify the Team Member
If a name is provided, match it against manager-context/team/ profiles.
If no name is specified, check the calendar for the next upcoming 1:1 meeting and identify the attendee.
If ambiguous:
Which team member? Your upcoming 1:1s are:
- [Name], [day] at [time]
- [Name], [day] at [time]
Load the team member's profile from manager-context/team/[name].md for:
- Their role, current projects, communication style
- Goals location (Notion page, Drive doc)
- Last review date and development areas
- Last 1:1 date and open items
If no profile exists:
⚠️ No profile found for [name]. Run /setup to build team context, or I'll work with what I can find from sources directly.
2. Surface Recent Work & Wins
Slack (last 7-14 days):
- Messages posted by this person in team/project channels
- Threads they've been active in
- Any shoutouts or recognition they received (search for their name + positive signals like "great", "shipped", "amazing", "thanks")
- Features shipped, PRs merged, deliverables completed (visible in public channels)
Google Drive:
- Documents they've recently created or edited
- Especially docs related to their projects or deliverables
Notion:
- Pages they've authored or updated recently
- Project status updates they've contributed to
What ships with it
3 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.
- 1mo ago First seen · 205 lines · 67 tokens per session scan A bec1abcaa785
one-on-one-prep is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (138 stars, last pushed 29d ago), licensed MIT. It adds 67 tokens to every session and 1,921 once invoked, about $0.0003 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 2026-08-30.
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