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 human-avatar/skills-for-humanity --skill s4h-emotional-resistance-diagnosisgit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-emotional-resistance-diagnosis)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-emotional-resistance-diagnosis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-emotional-resistance-diagnosis/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/human-avatar/skills-for-humanity/s4h-emotional-resistance-diagnosis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-emotional-resistance-diagnosis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.01283 |
| Opus 5 | $0.00037 | $0.00642 |
| Sonnet 5 | $0.00015 | $0.00257 |
| Haiku 4.5 | $0.00007 | $0.00128 |
Grade A, and why
s4h-emotional-resistance-diagnosis 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 9d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Emotional Resistance Diagnosis
Resistance is not a problem to overcome — it is a signal to decode. People resist for different reasons, and applying the wrong response to the wrong type makes it worse. Presenting more data to someone who is emotionally resistant does nothing. Acknowledging feelings with someone who has an intellectual objection is patronising. This skill identifies the source before prescribing the response.
Your Process
Step 1: Describe the Resistance Who is resisting, what are they saying explicitly, and how are they behaving? Get behaviorally specific — passive non-compliance, vocal objection, questions designed to slow things down, and political manoeuvring are different signals pointing to different sources.
Framing check: Confirm the specific resistance situation before continuing. State who is resisting, what they appear to be resisting, and in what context, in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of who is resisting, what they're resisting, and in what context]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different situation than read; incorporate the correction before proceeding
Step 2: Classify Each Instance Assign each type of resistance to one or more of these categories:
- Intellectual — they disagree with the reasoning, evidence, or conclusion. They think you're wrong.
- Emotional — they feel something important to them is at risk. They may not be able to articulate what, but something feels threatening.
- Political — a competing interest is served by the current state. Changing things costs them something real.
- Practical — they don't believe the plan can actually work. They've seen similar things tried and fail.
Step 3: Source of Each Type Dig to the specific source. Intellectual: which claim do they reject, and why? Emotional: what are they afraid of losing — status, security, relationships, credit? Political: whose interests benefit from the status quo, and how do they intersect with this person? Practical: what specifically do they believe will fail, and what informs that belief?
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.
- 9d ago First seen · 120 lines · 74 tokens per session scan A 44abeeef1c72
s4h-emotional-resistance-diagnosis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 1,283 once invoked, about $0.0004 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 2026-09-03.
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