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 anycap-ai/anycap --skill anycap-human-interactiongit clone --depth 1 https://github.com/anycap-ai/anycapWrote 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/anycap-ai/anycap/anycap-human-interaction)<a href="https://agentmods.dev/skills/anycap-ai/anycap/anycap-human-interaction"><img src="https://agentmods.dev/badge/skills/anycap-ai/anycap/anycap-human-interaction/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/anycap-ai/anycap/anycap-human-interaction"><img src="https://agentmods.dev/badge/skills/anycap-ai/anycap/anycap-human-interaction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 96 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- medium Excessive Agency · line 123 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00190 | $0.04253 |
| Opus 5.5 | $0.00076 | $0.01701 |
| Sonnet 5.5 | $0.00038 | $0.00851 |
| Haiku 4.5 | $0.00019 | $0.00425 |
Grade A, and why
anycap-human-interaction 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 today.
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 — 412 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AnyCap Human Interaction
Read this entire file before starting. Skipping sections leads to incorrect workflows -- each media type has different capabilities and constraints.
Workflow guide for collecting structured visual feedback from humans using AnyCap's annotation tool. This skill teaches you when and how to involve humans in your workflow through visual annotation and screen recording.
For CLI command reference, read the anycap-cli skill. For media generation workflows, read the anycap-media-production skill.
Prerequisites
AnyCap CLI must be installed and authenticated. Read the anycap-cli skill if setup is needed.
Two Core Scenarios
AnyCap annotation excels at two distinct review workflows. Choose the one that fits your situation:
| Scenario | Best for | Primary artifact | Highlight |
|---|---|---|---|
| URL / Web Page Review | Web pages, local dev servers, live UIs | Screen recording with narration | Browse, annotate, and narrate -- the recording captures everything |
| Image Collaborative Review | Generated images, screenshots, designs | Annotated image with merged feedback | Multiple reviewers annotate simultaneously in real-time |
Both scenarios support all annotation tools (Rect, Arrow, Point, Freehand) and text labels. The difference is in what you get back and how the review is conducted.
Command Quick Reference
# Blocking -- opens browser, waits for Done click, outputs result
anycap annotate <target> [-o output.png]
# Non-blocking -- starts background server, returns session info
anycap annotate <target> --no-wait [-o output.png]
# Poll for result after human confirms done
anycap annotate poll --session <session_id>
# Stop background server
anycap annotate stop --session <session_id>
# List all active sessions (useful for recovery after context loss)
anycap annotate list
<target> is auto-detected by content: image file, URL (http:// or https://), video file, or audio file.
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.
- today Changed eff809c7d668
- 21d ago Changed 30641fda975d
- 23d ago Changed e66598bee8ef
- 1mo ago Changed e3a6e8ace1fc
- 1mo ago First seen · 412 lines · 190 tokens per session scan A 2ed30b2b5a37
anycap-human-interaction is a skill published in the GitHub repository anycap-ai/anycap (45 stars, last pushed today), licensed MIT. It adds 190 tokens to every session and 4,253 once invoked, about $0.0008 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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