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 asimons81/hermes-field-kit --skill dont-lie-to-megit clone --depth 1 https://github.com/asimons81/hermes-field-kitWrote 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/asimons81/hermes-field-kit/dont-lie-to-me)<a href="https://agentmods.dev/skills/asimons81/hermes-field-kit/dont-lie-to-me"><img src="https://agentmods.dev/badge/skills/asimons81/hermes-field-kit/dont-lie-to-me/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/asimons81/hermes-field-kit/dont-lie-to-me"><img src="https://agentmods.dev/badge/skills/asimons81/hermes-field-kit/dont-lie-to-me.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 Excessive Agency · line 148 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 | $0.00043 | $0.02351 |
| Opus 5 | $0.00022 | $0.01175 |
| Sonnet 5 | $0.00009 | $0.00470 |
| Haiku 4.5 | $0.00004 | $0.00235 |
Grade A, and why
dont-lie-to-me 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 12d 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dont-lie-to-me
Overview
dont-lie-to-me is a claim-discipline layer for Hermes.
It exists for one recurring failure class: turning partial, missing, inferred, user-reported, or weak evidence into language that sounds verified.
The skill does not promise perfect truthfulness and does not make the model omniscient. It changes the process used before material claims are stated.
Core rule:
claim -> required evidence -> check -> state, qualify, or remove
Strong wording carries a stronger proof obligation. Missing evidence stays missing.
This skill governs claims about work. It does not reduce permissions already granted by the user, turn every task into a read-only audit, or require citations when citations are not otherwise needed.
When to Use
Use this skill when the user explicitly asks for evidence discipline, including requests such as:
/dont-lie-to-me- "Don't guess. Only tell me what you can verify."
- "Don't say it's fixed unless you actually tested it."
- "Separate what you know from what you're inferring."
- "Prove the important claims before you give me the answer."
- "If you can't verify something, say that instead of filling the gap."
This skill may also be loaded when the user's request clearly makes unsupported certainty itself the problem.
Do not load this skill merely because a task contains generic words such as check, research, accuracy, or verify when a narrower workflow already covers the need.
Do not load this skill for:
- Pure fiction, creative writing, roleplay, or imaginative brainstorming where factual verification is not the task.
- Ordinary ideation where the user explicitly wants hypotheses, possibilities, or speculative options.
- Citation formatting alone; use a citation-focused workflow instead.
- Tasks already governed by a narrower evidence contract unless the user explicitly invokes this skill as an additional constraint.
Evidence States
Before making a material claim, classify its support internally using one of these states:
What ships with it
6 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.
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.
- 12d ago First seen · 248 lines · 43 tokens per session scan A 0a76eace760f
dont-lie-to-me is a skill published in the GitHub repository asimons81/hermes-field-kit (125 stars, last pushed 2d ago), licensed Apache-2.0. It adds 43 tokens to every session and 2,351 once invoked, about $0.0002 per session on Opus 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
deliver
Prepare an inspectable Hardproof delivery during DELIVER with final scope, evidence, risks, rollback, and reproducible reporting.
design
Shape the smallest reversible Hardproof design from discovery evidence during DESIGN, including contracts, failures, and risks.
discover
Inspect a Hardproof run's request, repository, constraints, and unknowns during DISCOVERY before proposing a design.
implement
Execute approved Hardproof tasks during IMPLEMENT with focused tests, durable task updates, and scope-controlled code changes.
learn
Close a Hardproof run during LEARN by capturing safe provenance-linked lessons or recording an explicit reason to skip them.
orchestrate
Coordinate an active Hardproof run across discovery, design, planning, implementation, review, verification, delivery, and learning.