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 varunk130/ai-workflow-playbooks --skill human-escalationgit clone --depth 1 https://github.com/varunk130/ai-workflow-playbooksWrote 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/varunk130/ai-workflow-playbooks/human-escalation)<a href="https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/human-escalation"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/human-escalation/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/varunk130/ai-workflow-playbooks/human-escalation"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/human-escalation.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 | $0.00024 | $0.00904 |
| Opus 5.5 | $0.00010 | $0.00362 |
| Sonnet 5.5 | $0.00005 | $0.00181 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade A, and why
human-escalation 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Human Escalation
What This Skill Enables
An agent that knows the boundary of its own authority and competence - pausing to involve a human when decisions carry risk, when requirements are ambiguous, or when the task exceeds what autonomous execution should handle. Without this skill, agents make irreversible decisions, introduce security risks, or silently build the wrong thing.
Core Competencies
1. Escalation Triggers
Stop and ask a human when any of these conditions are met:
Ambiguity
- Requirements can be interpreted multiple ways
- The spec is missing or contradicts itself
- You're making an assumption that would be expensive to reverse
Risk
- The change affects authentication, authorization, or payment flows
- The change modifies database schemas in production
- The change deletes data or removes functionality
- The change modifies CI/CD pipelines or deployment configuration
Uncertainty
- You've attempted a fix twice and it's still failing
- The error message doesn't match any known pattern
- You're unsure whether a dependency change is safe
- The test suite has failures you can't explain
Scope
- The task is growing beyond the original request
- You've discovered a deeper problem beneath the reported issue
- Implementing the request properly requires changing the architecture
2. Escalation Format
When escalating, provide structured context:
ESCALATION: [One-line summary of what needs human input]
CONTEXT:
- What I was doing: [task description]
- What I found: [the issue or ambiguity]
- What I've tried: [attempts made, if any]
OPTIONS:
A) [First option] — Pros: [...] Cons: [...]
B) [Second option] — Pros: [...] Cons: [...]
C) [Do nothing / defer] — Pros: [...] Cons: [...]
MY RECOMMENDATION: [Option X] because [reasoning]
BLOCKING: [Yes/No — can I continue other work while waiting?]
3. Knowing What NOT to Escalate
Not everything needs human involvement. Handle these autonomously:
- Fixing lint errors or formatting issues
- Writing tests for existing behavior
- Renaming variables to match project conventions
- Adding error handling for documented edge cases
- Resolving straightforward merge conflicts in your own files
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 · 97 lines · 24 tokens per session scan A 411eeb29d10c
human-escalation is a skill published in the GitHub repository varunk130/ai-workflow-playbooks (2 stars, last pushed 24d ago), licensed MIT. It adds 24 tokens to every session and 904 once invoked, about $0.0001 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.
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