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-historical-precedent-analysisgit 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-historical-precedent-analysis)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-historical-precedent-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-historical-precedent-analysis/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-historical-precedent-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-historical-precedent-analysis.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 | $0.00069 | $0.01313 |
| Opus 5 | $0.00034 | $0.00656 |
| Sonnet 5 | $0.00014 | $0.00263 |
| Haiku 4.5 | $0.00007 | $0.00131 |
Grade A, and why
s4h-historical-precedent-analysis 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Historical Precedent Analysis
History doesn't repeat — but structures do. The error is searching for surface similarity (same industry, same technology, same geography) and missing structural similarity (same underlying dynamics, same constraint set, same incentive conflicts). Superficial precedents produce false confidence. Structural precedents produce genuine insight. This skill finds the real ones.
Your Process
Step 1: Abstract the Situation Strip away domain-specific language and surface details. What is the underlying structural pattern? Describe it in terms that could apply across industries and eras: a new entrant facing incumbents with switching-cost moats; a coalition with aligned goals but divergent interests trying to coordinate; a technology displacing a profession whose members control the adoption decision. State the situation in these structural terms — this is what you'll search for in history.
Framing check: Confirm the specific situation before continuing. State what you've identified — the actual situation being analyzed and its core structural pattern — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence structural framing of the situation]. 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: Search for Structural Precedents Deliberately look outside the obvious domain. The most obvious precedent (same industry, earlier decade) usually has the most surface similarity and the least structural insight — the surface differences are visible but the structural similarities are already assumed. Search across industries, eras, and scales for situations with the same underlying dynamics.
Before narrowing: Show the complete generated set to the user first. Use AskUserQuestion:
- Question: "I've identified [N] candidate precedents. Before I select the most structurally similar, are there any you'd flag as especially important, or any I've missed?"
- Header: "Prioritise"
- Options:
- Proceed with your selection — the set looks right
- Flag one — user will name a specific precedent to include
- Add a missing one — user will describe it
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 · 129 lines · 69 tokens per session scan A 2f148678efb3
s4h-historical-precedent-analysis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 1,313 once invoked, about $0.0003 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.
Other skills, from other repositories
decision-making-under-pressure
Provides practical habits for making better decisions faster -- reframing problems before solving them, knowing when to stop deliberating, balancing intuition with analysis, resisting 'just this once' compromises, and breaking overthinking cycles. Use when facing a high-stakes choice with incomplete data, sensing that…
flow-state
Optimizes individual and team productivity using Csikszentmihalyi's flow state framework, covering the conditions for flow (clear goals, immediate feedback, challenge-skill balance), the four-stage flow cycle, and organizational flow design. Use when auditing personal or team focus time, diagnosing productivity loss…
stoic-right-action
Applies Stoic ethics of right action to entrepreneurial decision-making, covering the four cardinal virtues (courage, justice, temperance, wisdom), ethical leadership under pressure, and the discipline of choosing the harder right over the easier wrong. Use when facing ethical dilemmas in business, building a…
bakeoff
Turn one decision into a judged tournament of solutions, then pick the best. Given a problem, design choice, or a suggestion you want cross-verified, it generates diverse candidate solutions, auto-derives the evaluation dimensions for THAT problem (so you don't have to know what to score on), judges every candidate…
balanced-scorecard
Translate strategy into metrics across Financial, Customer, Internal Process, and Learning & Growth perspectives.
customer-journey-map
Visualize every touchpoint a customer has with a product or service — stages, actions, emotions, pain points, opportunities.