Borrowing it
Nothing to install: this file belongs to agno-agi/context. 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/agno-agi/context/main/.agents/skills/extend-agent/SKILL.mdgit clone --depth 1 https://github.com/agno-agi/contextWrote 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/agno-agi/context/extend-agent)<a href="https://agentmods.dev/skills/agno-agi/context/extend-agent"><img src="https://agentmods.dev/badge/skills/agno-agi/context/extend-agent/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/agno-agi/context/extend-agent"><img src="https://agentmods.dev/badge/skills/agno-agi/context/extend-agent.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 | $0.00110 | $0.03147 |
| Opus 5.5 | $0.00044 | $0.01259 |
| Sonnet 5.5 | $0.00022 | $0.00629 |
| Haiku 4.5 | $0.00011 | $0.00315 |
Grade B, and why
extend-agent scanned grade B with 2 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 2mo 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
- Live container reachable: `curl -sSf http://localhost:8000/health` returns 200. If not, ask the user to `docker compose up -d --build` first. (`docker compose ps` is unreliable from worktrees or alternate clones — trus Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Live container reachable: `curl -sSf http://localhost:8000/health` returns 200. If not, ask the user to `docker compose up -d --build` first. (`docker compose ps` is unreliable from worktrees or alternate clones — trus How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extend an Agent
Coding-agent workflow — a
/slash-commandyour coding agent (Claude Code, Codex, …) runs while developing this repo. Not a runtime skill the deployed @context agent runs; those live inskills/.
You are recursively extending a target agent with the user in the driver's seat. Each iteration: the user names a change, you implement it with an Agno-aware eye (using the agno-docs MCP for any toolkit / API research), the change is verified against the live agent, then you ask if there's more to do. Stop when the user says they're done.
This is the user-driven half of the iteration loop. The autonomous half lives in the improve-agent skill — Claude derives probes from the agent's INSTRUCTIONS and hardens behavior with no user input. Use this skill to change the agent (add tools, add capabilities, refine the prompt, fix a known bug). Run improve-agent afterward to confirm nothing else regressed.
The platform is on http://localhost:8000 with hot-reload enabled (RUNTIME_ENV=dev), so edits to agents/<slug>.py are picked up by uvicorn within ~1s. Edits to app/main.py (e.g. registering a new sub-agent) require a container restart — Step 5 covers this.
0. Preconditions
-
Live container reachable:
curl -sSf http://localhost:8000/healthreturns 200. If not, ask the user todocker compose up -d --buildfirst. (docker compose psis unreliable from worktrees or alternate clones — trust the health probe.) -
Live container is bound to this checkout — otherwise hot-reload won't see your edits:
docker inspect context-api --format '{{range .Mounts}}{{.Source}}{{"\n"}}{{end}}' | grep -F "$(pwd)"Empty result = the container's
/appis bound to a different repo path. Eithercdto that repo or restart the container from this directory (docker compose down && docker compose up -d --build). -
Ask the user for the target agent slug (usually
context— the one registered agent). -
Recommend the user create a feature branch (
git checkout -b extend/<slug>-$(date +%Y%m%d)) so any wrong turns are easy to revert.
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.
- 2mo ago First seen · 189 lines · 110 tokens per session scan B 34dcf8d33d0a
extend-agent is a skill published in the GitHub repository agno-agi/context (13 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 110 tokens to every session and 3,147 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
codex-interactive-capability-map
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video-prompt
Directing contract for editable shots and continuous performance segments.
openlore
Query and publish to an OpenLore knowledge repository over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.
cinematic-storyboard
A storyboard-planning guide for turning a script into reviewable video-shot plans. It connects each shot to the story event, visual focus, movement, space, and physical result.
director-review
A review process for checking video prompts and generated images against story, action, camera, setting, timing, and continuity requirements. It requires visual evidence before declaring an image or sequence correct.
story-causality
A story-planning guide for linking each scene's goal, trigger, action, result, and next cause. It also sets boundaries for dates, character knowledge, evidence, dialogue, and the time needed for each scene.