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 EvoClaw/amplify --skill analysis-storyboard-designgit clone --depth 1 https://github.com/EvoClaw/amplifyWrote 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/evoclaw/amplify/analysis-storyboard-design)<a href="https://agentmods.dev/skills/evoclaw/amplify/analysis-storyboard-design"><img src="https://agentmods.dev/badge/skills/evoclaw/amplify/analysis-storyboard-design/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/evoclaw/amplify/analysis-storyboard-design"><img src="https://agentmods.dev/badge/skills/evoclaw/amplify/analysis-storyboard-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00035 | $0.00942 |
| Opus 5 | $0.00017 | $0.00471 |
| Sonnet 5 | $0.00007 | $0.00188 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
analysis-storyboard-design 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 10d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analysis Storyboard Design (Sub-skill of Method Framework Design)
Overview
Applies to Type D and Type H projects. A discovery project without a storyboard produces scattered, shallow analyses that fail to tell a coherent scientific story. Design the narrative arc before running the first analysis.
Step-by-Step Storyboard Design
1. Define Main Story Line
Articulate the core narrative:
- Scientific question: What are we trying to understand?
- Expected finding: What do we predict the data will show?
- Why it matters: What changes if this finding holds?
Write as a single paragraph: "We investigate [question]. We expect to find [prediction] because [reasoning]. This matters because [impact]."
2. Define Supporting Lines
Design 2–4 supporting story lines. Each must validate, extend, or contextualize the main line:
| Line | Purpose | Relationship to Main |
|---|---|---|
| Supporting Line 1 | (validates main finding from different angle) | Validation |
| Supporting Line 2 | (explores mechanism or cause) | Explanation |
| Supporting Line 3 | (tests boundary conditions) | Robustness |
| Supporting Line 4 | (reveals unexpected patterns) | Extension |
Minimum 2 supporting lines. Fewer produces an incomplete story.
3. Plan Figures, Tests, and Conclusions per Line
For each story line (main + supporting), specify:
- Planned figures/tables — what visualization, what it shows
- Statistical tests — what test, what hypothesis it evaluates
- Expected conclusion — what result supports the line, what result refutes it
Present to user for confirmation.
4. Define Sufficiency Criteria
IRON LAW: ANALYSIS MUST BE COMPREHENSIVE. NO SHORTCUTS.
Every box must be checked before the analysis plan is approved:
- □ Descriptive analysis covers complete data overview?
- □ Main hypothesis tested from multiple angles?
- □ Exploratory analysis planned for unexpected patterns?
- □ All supporting lines connect back to main story?
- □ At least 4–6 content points with planned figures/tables?
- □ Confounders identified and addressed?
- □ Statistical support sufficient for each claim?
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.
- 10d ago First seen · 106 lines · 35 tokens per session scan A 77bf81c6c4b6
analysis-storyboard-design is a skill published in the GitHub repository EvoClaw/amplify (12 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 942 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.
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