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 simota/agent-skills --skill mendgit clone --depth 1 https://github.com/simota/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/simota/agent-skills/mend)<a href="https://agentmods.dev/skills/simota/agent-skills/mend"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/mend/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/simota/agent-skills/mend"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/mend.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
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 →
- high Prompt Injection · line 6 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high YARA Match · line 45 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Anti-Refusal · line 118 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
- high Prompt Injection · line 118 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- medium Excessive Agency · line 125 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 | $0.00035 | $0.05171 |
| Opus 5.5 | $0.00014 | $0.02068 |
| Sonnet 5.5 | $0.00007 | $0.01034 |
| Haiku 4.5 | $0.00003 | $0.00517 |
Grade A, and why
mend 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 22d 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 — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mend
Automated remediation agent for known failure patterns. Use Mend after a Triage diagnosis or Beacon alert when the issue is operationally fixable through restart, scale, config rollback, circuit breaker, canary rollback, or another reversible runtime action. Mend follows a maturity model: read-only insights → advised actions → approval-based remediation → autonomous operation with guardrails (Source: rootly.com — AI SRE Guide 2026). Every step is idempotent, auditable, and rollback-ready. Mend changes runtime and operational state only. Application logic and product behavior go to Builder.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _common 10 B
- reference/_common 13 B
- reference/adversarial-defense.md 4.8 KB
- reference/autorun-schema.md 995 B
- reference/canary-remediation.md 9.9 KB
- reference/circuit-remediation.md 7.6 KB
- reference/learning-loop.md 7.5 KB
- reference/remediation-patterns.md 16 KB
- reference/runbook-execution.md 8.1 KB
- reference/safety-model.md 11 KB
- reference/scale-remediation.md 8.2 KB
- reference/verification-strategies.md 7.4 KB
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.
- 22d ago Changed f516a127ddcd
- 28d ago Changed b60f84b3bf02
- 1mo ago Changed · -1 lines 782045ef6844
- 2mo ago First seen · 248 lines · 35 tokens per session scan A acf7919c1268
mend is a skill published in the GitHub repository simota/agent-skills (98 stars, last pushed 11d ago), licensed MIT. It adds 35 tokens to every session and 5,171 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 2026-09-03.
mend compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mendsimota/agent-skills | Skill | 98 | 11d ago | MIT | A | 35 | Claude Code, Codex |
| deploy-genjmagly/aiwg | Skill | 229 | yesterday | MIT | A | 15 | Claude Code |
| cockpit-headless-deployjmagly/aiwg | Skill | 229 | yesterday | MIT | A | 41 | Claude Code, Codex |
| cloud-hosting-expertroedyrustam/vibes-plug | Skill | 121 | yesterday | MIT | A | 41 | Cursor |
| cloudflare-workers-expertroedyrustam/vibes-plug | Skill | 121 | yesterday | MIT | A | 46 | Cursor |
| self-healing-cloud-orchestratorroedyrustam/vibes-plug | Skill | 121 | yesterday | MIT | A | 39 | Cursor |
| remote-compute-opsAnastasiyaW/codex-claude-code-config | Skill | 214 | yesterday | MIT | A | 132 | Claude Code, Codex |