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-narrative-frame-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-narrative-frame-analysis)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-narrative-frame-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-narrative-frame-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-narrative-frame-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-narrative-frame-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 | $0.00058 | $0.01085 |
| Opus 5 | $0.00029 | $0.00543 |
| Sonnet 5 | $0.00012 | $0.00217 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
s4h-narrative-frame-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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narrative Frame Analysis
Frames are invisible until named. The same facts support radically different conclusions depending on who is the protagonist, what counts as the problem, and what counts as success. Most communication failures are framing failures — not evidence failures. Reframing does not change the facts; it changes which facts are salient and which conclusions they support.
Your Process
Step 1: Name the Current Frame Make the implicit explicit. Who is the protagonist in the current frame? What is the problem being solved? What counts as a successful outcome? What is the frame's implicit villain or antagonist?
Framing check: Confirm the specific situation and its dominant frame before continuing. State what you've identified — the actual narrative or discourse being analysed, who the current protagonist is, and what the core tension appears to be — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the situation and its current frame]. 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: Identify What the Current Frame Hides Every frame foregrounds some things and backgrounds others. What does the current frame make invisible, irrelevant, or unthinkable? Who loses standing in this frame? What solutions become impossible to see?
Step 3: Generate 3–4 Alternative Frames For each alternative, change at least one of: protagonist, problem definition, success criteria, or time horizon. Assign each alternative a short name.
Step 4: Assess Each Alternative What does each alternative frame reveal that the current frame hides? Who gains standing? What solutions become visible? What previously central concerns become peripheral?
Step 5: Select the Most Useful Frame
Before narrowing: Show the complete set of alternative frames generated in Step 3 to the user first. Use AskUserQuestion:
- Question: "I've identified [N] alternative frames. Before I select the most useful one, are there any you'd flag as especially promising, or any framing I've missed?"
- Header: "Prioritise"
- Options:
- Proceed with your selection — the set looks right
- Flag one — user will name a specific frame to prioritise
- Add a missing one — user will describe an alternative frame to include
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 · 98 lines · 58 tokens per session scan A 680afc4cac4c
s4h-narrative-frame-analysis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,085 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.
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