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 itallstartedwithaidea/agent-skills --skill self-healing-agentsgit clone --depth 1 https://github.com/itallstartedwithaidea/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/itallstartedwithaidea/agent-skills/self-healing-agents)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/self-healing-agents"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/self-healing-agents/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/itallstartedwithaidea/agent-skills/self-healing-agents"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/self-healing-agents.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 | $0.00027 | $0.02045 |
| Opus 5.5 | $0.00011 | $0.00818 |
| Sonnet 5.5 | $0.00005 | $0.00409 |
| Haiku 4.5 | $0.00003 | $0.00204 |
Grade A, and why
self-healing-agents 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Healing Agents
Part of Agent Skills™ by googleadsagent.ai™
Description
Self-Healing Agents are autonomous systems that detect their own failure modes and self-correct without human intervention. In production environments, agent failures are not exceptional — they are expected. Network calls timeout, APIs return unexpected schemas, models hallucinate confidently, and tool outputs violate assumptions. The difference between a prototype and a production agent is the ability to recover gracefully from every category of failure.
This skill encodes the self-healing patterns developed for the Buddy™ agent at googleadsagent.ai™, where autonomous Google Ads analysis must complete reliably even when upstream APIs change, rate limits are hit, or model outputs contain structural errors. The system operates on a detect-diagnose-repair cycle that mirrors biological immune responses: identify the pathogen, classify the threat, and deploy the appropriate countermeasure.
Self-healing is not merely retry logic. It encompasses error classification, strategy mutation (retrying with a different approach rather than the same one), fallback model selection, output validation with automatic repair, and graceful degradation when full recovery is impossible. Agents built with these patterns achieve 99%+ task completion rates in production.
Use When
- Building agents that must operate autonomously without human oversight
- Tool calls or API integrations are unreliable or subject to rate limits
- Model outputs must conform to strict schemas and occasionally don't
- Long-running workflows cannot afford to fail mid-execution
- You need to maintain SLA commitments for agent-powered features
- The agent must handle novel error types it hasn't encountered before
How It Works
graph TD
A[Agent Action] --> B[Output Validation]
B -->|Valid| C[Continue Execution]
B -->|Invalid| D[Error Classifier]
D --> E{Error Type}
E -->|Transient| F[Retry with Backoff]
E -->|Structural| G[Mutate Strategy]
E -->|Model Error| H[Fallback Model]
E -->|Unrecoverable| I[Graceful Degradation]
F --> J{Retry Budget Remaining?}
J -->|Yes| A
J -->|No| G
G --> K[Modified Prompt/Approach]
K --> A
H --> L[Alternative Model Execution]
L --> B
I --> M[Partial Result + Error Report]
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 · 219 lines · 27 tokens per session scan A 385c193168e7
self-healing-agents is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (44 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 2,045 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 2026-08-30.
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