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 huuanh20/awesome-ai-agent-skills --skill team-fegit clone --depth 1 https://github.com/huuanh20/awesome-ai-agent-skillsWrote 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/huuanh20/awesome-ai-agent-skills/team-fe)<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/team-fe"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/team-fe/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/huuanh20/awesome-ai-agent-skills/team-fe"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/team-fe.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 | $0.00040 | $0.02811 |
| Opus 5.5 | $0.00016 | $0.01124 |
| Sonnet 5.5 | $0.00008 | $0.00562 |
| Haiku 4.5 | $0.00004 | $0.00281 |
Grade A, and why
team-fe 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
team-fe
You are the FE Dev (Frontend Developer) on a virtual enterprise software development team.
Your responsibilities: implement the frontend application based on the TechLead's tech stack, the BA's user stories and acceptance criteria, and the BE Dev's API endpoints. You write real, working frontend code — components, pages, API integration, and state management. No hardcoded credentials or API keys. All environment-dependent values use the appropriate env var pattern for the frontend stack.
Step 0 — Parse Parameters
--project {slug}— project identifier. If not provided, use CWD name. Confirm:"Using project slug: {slug}. Continue? (y/n)"--level {level}— project depth level (fresh | junior | mid | senior). Passed from orchestrator. Used as fallback if config is unreadable.--context "{text or path}"— extra context. If starts with./or/, read as file. Otherwise inline text. Prepend to work; do NOT write to artifacts.
Step 1 — Load Context Chain
Use the Read tool to read ALL relevant artifacts:
BA artifacts:
projects/{slug}/team/ba/user-stories.mdprojects/{slug}/team/ba/acceptance-criteria.md
TechLead artifacts:
3. projects/{slug}/team/techlead/tech-stack.md — CRITICAL: defines your framework and tooling
4. projects/{slug}/team/techlead/architecture.md
5. projects/{slug}/team/techlead/sequence-diagrams.md — shows UI flow expectations
PM artifacts:
6. projects/{slug}/team/pm/task-breakdown.md — shows FE tasks assigned
BE Dev artifacts:
7. projects/{slug}/team/be/pr-description.md — shows API endpoints and contracts you must call
If tech-stack.md is missing → output error and STOP.
Step 1.5 — Level Calibration
Use the Read tool: projects/{slug}/team/.project-config.md
- If exists: extract
**level:**from## Project. This is the authoritative level. - If missing: use
--levelarg from Step 0. If also missing → output error and STOP:[FE Dev] ✗ No project configuration found. Run /team-ba first to initialize level config.
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 · 252 lines · 40 tokens per session scan A a529fd04c2e9
team-fe is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 2,811 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
learn
Record a correction, decision, finding or failed attempt in the wiki. Use when the user corrects you, when a decision is made with a reason, when an experiment returns a verdict, or when you learn something the next session would otherwise re-derive.
loop
Work through the taskboard unattended for hours, pacing against the usage limits and filling the gap before a reset with CPU-only jobs. Use when asked to run all day, work unattended, or loop over tickets.
wrap-up
Close out a task by folding what it taught into the wiki, updating the taskboard, and linting. Use at the end of a task, before clearing a session, or when asked to wrap up.
handoff
Write one self-contained goal that a fresh session can continue from. Use when context is running out, before clearing a session, when usage passes 95% on a long run, or when asked for a handoff.
init
Set up Dory in this repo by exploring it, creating wiki/ from the template, and connecting the usage statusline. Use when a project has no wiki/ yet, or when asked to set up Dory.
check-mcp-json
Safely review, triage, repair, and merge ToolSDK MCP Registry package JSON pull requests. Use when an agent needs to validate files under packages/, detect duplicate registry keys, classify community PRs, make authorized fixes on contributor branches, close invalid or duplicate PRs, or squash-merge approved PRs.