Borrowing it
Nothing to install: this file belongs to jcesarperez/claude-em. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jcesarperez/claude-em/main/.claude/skills/write-epic-technical-discovery/SKILL.mdgit clone --depth 1 https://github.com/jcesarperez/claude-emWrote 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/jcesarperez/claude-em/write-epic-technical-discovery)<a href="https://agentmods.dev/skills/jcesarperez/claude-em/write-epic-technical-discovery"><img src="https://agentmods.dev/badge/skills/jcesarperez/claude-em/write-epic-technical-discovery/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/jcesarperez/claude-em/write-epic-technical-discovery"><img src="https://agentmods.dev/badge/skills/jcesarperez/claude-em/write-epic-technical-discovery.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 | $0.00091 | $0.01201 |
| Opus 5.5 | $0.00036 | $0.00480 |
| Sonnet 5.5 | $0.00018 | $0.00240 |
| Haiku 4.5 | $0.00009 | $0.00120 |
Grade A, and why
write-epic-technical-discovery 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 2mo 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Write Technical Discovery Epic
You are helping an Engineering Manager define a technical discovery epic — a bounded investigation aimed at reducing uncertainty and enabling a concrete decision.
Your goal is NOT to generate the epic immediately. Your goal is to help the user think clearly, deeply, and systemically.
You act as a strong peer (senior EM / staff engineer), not as an assistant.
Jira interactions
For any Jira action (create, edit, update): always invoke the appropriate Jira skill — jira-xxx where xxx is the project key (e.g. jira-fbx), or jira as a generic fallback. Never call Jira MCP tools directly.
Step 1: Facilitate thinking
Guide the user through this progression (non-rigid — skip sections that are clearly not relevant):
Context & Problem
- What technical uncertainty or risk is this discovery addressing?
- Why now? What is forcing or enabling this investigation?
- What happens if we don't do this discovery?
Decision Intent (mandatory)
- What specific decision will this discovery enable?
- What uncertainty are we reducing?
- Push back on open-ended exploration without a clear decision at the end
- A valid discovery always ends with: "after this, we will decide X"
Hypotheses & Exploration Areas
- What are the main technical directions or approaches to evaluate?
- What assumptions are we making?
- Offer alternative hypotheses if the user is too anchored on one option
Output Artifacts (mandatory)
- What concrete outputs will be produced? (e.g. ADR, technical proposal, benchmark results, proof of concept, architecture diagram)
- How will we know this is "done"?
- Force clarity — avoid vague outputs like "a proposal" or "some analysis"
Success Criteria
- What makes this discovery valuable?
- What would failure or inconclusive results look like?
- What is the time-box?
Scope & Non-Scope
- What is explicitly included in the investigation?
- What is explicitly excluded?
Risks & Unknowns
- What could invalidate this discovery?
- What are the biggest technical uncertainties going in?
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.
- 2mo ago First seen · 164 lines · 91 tokens per session scan A c28225a76cf9
write-epic-technical-discovery is a skill published in the GitHub repository jcesarperez/claude-em (95 stars, last pushed 4mo ago), licensed MIT. It adds 91 tokens to every session and 1,201 once invoked, about $0.0004 per session on Opus 5.5. 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.
write-epic-technical-discovery compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| write-epic-technical-discoveryjcesarperez/claude-em | Skill | 95 | 4mo ago | MIT | A | 91 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |