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 marcusgoll/Spec-Flow --skill epic-meta-promptinggit clone --depth 1 https://github.com/marcusgoll/Spec-FlowWrote 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/marcusgoll/spec-flow/epic-meta-prompting)<a href="https://agentmods.dev/skills/marcusgoll/spec-flow/epic-meta-prompting"><img src="https://agentmods.dev/badge/skills/marcusgoll/spec-flow/epic-meta-prompting/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/marcusgoll/spec-flow/epic-meta-prompting"><img src="https://agentmods.dev/badge/skills/marcusgoll/spec-flow/epic-meta-prompting.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 | $0.00000 | $0.01114 |
| Opus 5.5 | $0.00000 | $0.00446 |
| Sonnet 5.5 | $0.00000 | $0.00223 |
| Haiku 4.5 | $0.00000 | $0.00111 |
Grade A, and why
epic-meta-prompting 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 1mo 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Epic Meta-Prompting Skill
Generate research and planning prompts for epic workflows using isolated sub-agents.
Purpose
Use meta-prompting to create research and planning pipelines via /create-prompt and /run-prompt, preventing context pollution through isolated execution.
When to Invoke
- During
/epicStep 3 (Research & Planning phase) - After epic specification is complete and reviewed
- Skip if resuming past the planning phase
Research Prompt Generation
/create-prompt "Research technical approach for: [epic objective]"
The create-prompt skill will:
- Detect purpose: Research
- Ask contextual questions (depth, sources, output format)
- Generate research prompt in
.prompts/001-[epic-slug]-research/ - Reference relevant project docs (@docs/project/tech-stack.md)
- Specify XML output format with metadata
Auto-execute research prompt:
/run-prompt 001-[epic-slug]-research
Research outputs:
.prompts/001-[epic-slug]-research/research.md- Contains: findings, confidence levels, dependencies, open questions, assumptions
Copy and Commit Research
# Copy research.md to epic directory
cp .prompts/001-${EPIC_SLUG}-research/research.md epics/${EPIC_SLUG}/research.md
# Extract metadata for commit message
FINDINGS_COUNT=$(xmllint --xpath 'count(//finding)' epics/${EPIC_SLUG}/research.md)
CONFIDENCE=$(xmllint --xpath 'string(//confidence_level)' epics/${EPIC_SLUG}/research.md)
OPEN_QUESTIONS=$(xmllint --xpath 'count(//open_question)' epics/${EPIC_SLUG}/research.md)
# Commit research
git add .prompts/001-${EPIC_SLUG}-research/
git add epics/${EPIC_SLUG}/research.md
git commit -m "docs(epic-research): complete technical research for ${EPIC_SLUG}
Findings: ${FINDINGS_COUNT}
Confidence: ${CONFIDENCE}
Open questions: ${OPEN_QUESTIONS}
Next: Planning phase"
Alternative: /meta:enforce-git-commits --phase "epic-research"
Planning Prompt Generation
/create-prompt "Create implementation plan based on research"
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.
- 1mo ago First seen · 154 lines · 0 tokens per session scan A a4e75ab7dade
epic-meta-prompting is a skill published in the GitHub repository marcusgoll/Spec-Flow (96 stars, last pushed 23d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,114 tokens. 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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