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bip-epic-check
Review an EPIC issue markdown file for strategic clarity, cost soundness, and scope discipline
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Review an EPIC issue markdown file for strategic clarity, cost soundness, and scope discipline
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Check remote server CPU, memory, and GPU availability via SSH
Cold-start into a worktree/clone from a fresh conversation — read the PR, issue, and any status files, figure out where things stand, then STOP and ask the user what to do next. Use for a fresh conversation dropped into a bip-spawn or bip-epic-spawn worktree/clone that already has history (a PR, an in-progress phase, or a stalled worker).
Quick poll of tracked EPICs and code repos for new manuscript-relevant results
Persist manuscript session state before context reset
Cold-start for a manuscript session — the paper is the source of truth and shared context; discuss results, orchestrate research through issues/PRs, and update the paper as threads complete
Spawn a Claude session in a clone for an EPIC issue
| name | bip-epic-check |
| description | Review an EPIC issue markdown file for strategic clarity, cost soundness, and scope discipline |
| allowed-tools | Agent, Bash, Read, Edit |
Review an EPIC issue markdown file for the qualities that matter at the strategic/research level. EPICs are roadmaps that guide months of work — they are NOT implementation tasks.
This skill complements /bip-issue-check (which reviews implementation-
ready issues for data paths, column names, test configs). /bip-epic-check
reviews research direction documents for the failure modes that waste
months, not hours.
/bip-epic-check ISSUE-my-epic.md
/bip-epic-check # uses most recently discussed ISSUE-*.md
$ARGUMENTS is provided, use that as the file pathRead the EPIC file. Also check for:
CLAUDE.md in the repo root (project conventions)# If the EPIC targets a specific repo, check its existing EPICs
gh issue list --repo <org/repo> --label "EPIC" --limit 5 --json number,title
Use the Agent tool to launch a general-purpose subagent that reads the EPIC file and checks the following. The subagent should verify claims by reading referenced files, running cost calculations, and checking existing repo structure.
Pass the full EPIC text and any context from Step 2 to the subagent.
Objective vs strategy: Does the EPIC clearly distinguish the optimization objective (what we're maximizing) from the search strategy (how we navigate the space)? A common failure is claiming a "new objective" when only the search strategy changed, or vice versa. Flag as HIGH if conflated.
Novelty claim: Is the "what's novel" claim precise? Can you tell exactly which existing method does the closest thing and what the delta is? Vague novelty ("combines X and Y") without explaining why no one has done this is a red flag.
Achievability: Is there a plausible argument that this can work? Not a proof, but at least a reason to believe the approach isn't doomed (e.g., a related method works in a simpler setting, a theoretical argument, or preliminary evidence).
"What this is NOT" section: Is there one? EPICs attract scope creep because they're long-running. Explicitly listing out-of-scope items prevents drift. Flag as HIGH if missing.
Phase boundaries: Could someone tell, for each phase, whether it's done or not? Each phase needs a concrete gate (a test, a metric threshold, a comparison). "Implement X" is not a gate; "X produces identical output to reference on test case Y" is.
Phase dependencies: Are co-dependencies between components explicit? If Phase N requires something from Phase M that isn't listed as a prerequisite, flag as HIGH.
This is the single highest-value check. EPICs routinely wave hands at computational cost with analogies ("same pattern as X") that don't survive arithmetic.
Back-of-envelope verification: For every complexity claim (O(...) notation, "same as X", "< Nx slower"), work out the actual cost on a concrete example. If the EPIC says "O(n * tree_pass)", compute what that means for n=16, n=64, n=256. If it says "< 10x wall time", check whether the stated complexity allows that. Flag as CRITICAL if a cost claim is wrong by > 2x.
Scaling cliffs: Are there operations whose cost changes qualitatively at some scale? (e.g., fits in cache at n=32 but not n=64; profile size grows polynomially but DP cost is multiplicative). Flag as HIGH if a scaling cliff exists but isn't discussed.
Success criteria vs cost: Do the success criteria (especially wall-time criteria) survive the cost analysis? If criterion says "< 10x" but the complexity analysis shows 32x, flag as CRITICAL.
Risks and mitigations: Is there a section? At minimum, the EPIC should identify the top 3 ways the approach could fail and name an early signal for each. Flag as HIGH if missing.
Kill criterion: Which success criterion catches fundamental failure earliest? If the first real test is in the final phase, the EPIC risks months of work before discovering the approach doesn't work. Flag as HIGH if the earliest meaningful accuracy test is in the last phase.
Failure modes specific to this approach: Generic risks ("might be slow", "might not be accurate") don't count. The risks should be specific to the approach — failure modes that wouldn't apply to alternative approaches. (e.g., "profile blowup" is specific to profile-based methods; "might not beat PRANK" is generic.)
Author attributions: Are papers correctly attributed? Pay special attention to the PI's own papers — don't use generic "et al." for first-author work. Check that reference IDs (bip keys) are correct if provided.
Characterization of related work: For each method described in "Connection to existing work", is the characterization accurate? Check for common mischaracterizations: saying a method "doesn't do X" when it does, or claiming a method uses technique Y when it uses Z.
Check for the following sections (based on established EPIC patterns in matsengrp repos). Flag missing sections as MEDIUM:
If the EPIC proposes a greedy or incremental algorithm, check whether the ordering/scheduling of operations is discussed. Greedy algorithms are notoriously order-sensitive. Flag as HIGH if the EPIC proposes incremental construction but defers order discussion to the final phase.
Present findings grouped by severity:
For each finding, state:
Present findings to the user. Do NOT edit the file without explicit approval — EPICs represent strategic decisions that require human judgment.
After the user approves specific fixes, apply them to the file.
If the user wants to submit the EPIC as a GitHub issue, invoke
/bip-issue-file with the file path. EPICs are often kept as local
markdown files and submitted later, so do not assume submission.