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 Sistema2D/FrameCode-VibeWork --skill agent-hermesgit clone --depth 1 https://github.com/Sistema2D/FrameCode-VibeWorkWrote 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/sistema2d/framecode-vibework/agent-hermes)<a href="https://agentmods.dev/skills/sistema2d/framecode-vibework/agent-hermes"><img src="https://agentmods.dev/badge/skills/sistema2d/framecode-vibework/agent-hermes/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/sistema2d/framecode-vibework/agent-hermes"><img src="https://agentmods.dev/badge/skills/sistema2d/framecode-vibework/agent-hermes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Agent Snooping · line 61 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00039 | $0.00539 |
| Opus 5.5 | $0.00016 | $0.00216 |
| Sonnet 5.5 | $0.00008 | $0.00108 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
agent-hermes 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Agent Hermes
Purpose
Performance-focused agent profile for one small, safe, measurable optimization. It works on demand or when called by an external scheduler; the scheduler is optional.
Activation Triggers
Load when the task involves measurable bottlenecks, runtime efficiency, bundle size, caching, latency, repeated expensive work, slow startup, performance regressions, or the Portuguese equivalents: desempenho, otimizar, otimização, lentidão, gargalo, tempo de carregamento, latência, cache, bundle, or inicialização lenta.
Mission
Find and implement exactly one focused optimization that preserves behavior and has measurable or well-supported performance value. If no evidence-backed improvement exists, stop without changing files.
Mandatory Governance
- Follow
AGENTS.md,PROJECT.md(performance),PLANNING.md, andTESTS.md. - Create or use an active plan before modifying files.
- Update changelog and validation evidence before closure.
- For durable codebase-specific performance learning, update a canonical page or create a sourced
fcvw/wiki@1page underwiki/(type: agentnotes) with a collision-resistant ID; do not rely on a shared fixed journal filename.
Boundaries
Stop before implementation if the optimization requires:
- new dependencies;
- architecture change;
- package or build configuration changes without explicit plan scope;
- public behavior change;
- speculative optimization of a cold path;
- broad refactoring.
Inspect Order
- Hot paths and repeated expensive work.
- Avoidable rendering or recomputation.
- Inefficient IO, network calls, parsing, or serialization.
- Cache or memoization opportunities with clear invalidation.
- Bundle or startup cost with evidence.
Output Required
## Hermes Performance Pass
- Skill loaded: `skills/agent-hermes/SKILL.md`
- Opportunity selected:
- Evidence:
- Files in scope:
- Expected impact:
- Validation:
- Knowledge update: `yes` / `no`
Validation and exit
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 Changed · -6 lines · +28 tokens per session ee49fc87f37e
- 2mo ago First seen · 73 lines · 11 tokens per session scan A a5d24ac213c2
agent-hermes is a skill published in the GitHub repository Sistema2D/FrameCode-VibeWork (29 stars, last pushed 29d ago), licensed Apache-2.0. It adds 39 tokens to every session and 539 once invoked, about $0.0002 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.
Other skills, from other repositories
evaluate-pattern-adoption
Run or plan this repository's pattern-adoption evidence evaluation locally with signed-in Codex agents. Use when asked to refresh stale evidence, assess stable or exploratory patterns, evaluate one or all catalog patterns, discover possible new patterns, or prepare a reviewable evidence PR without model-backed GitHub…
fix-issue
Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue via PR. Includes prevention analysis to…
error-analysis
Evals-first error analysis for LLM apps: clusters real Langfuse or JSONL traces into a human-confirmed failure taxonomy with counts, then recommends binary pass/fail evals for recurring named modes. Use to learn what to measure before writing evals. Not for CI failures.
ci-debug
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for…
monitoring-observability
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (astype, scorecurrentspan, shouldexportspan, LangfuseMedia), and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
paired-probe
Refuse a verdict a probe did not earn. Runs a check where the fault IS present and where it is NOT, and blocks the answer when both arms print the same thing, because a check that cannot disagree with you has measured nothing. Also catches the zero-sample sweep that reads as "clean" and the swallowed error that reads…