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 agentmods add skills/soulcodex/agentic/github-issue-planningnpx skills add soulcodex/agentic --skill github-issue-planninggit clone --depth 1 https://github.com/soulcodex/agenticWhat 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 | $0.00062 | $0.00827 |
| Opus 5 | $0.00031 | $0.00413 |
| Sonnet 5 | $0.00012 | $0.00165 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
github-issue-planning 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 2d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Issue Planning Skill
Use this skill when planning work tied to a GitHub issue and the plan should be persisted on that issue for team visibility.
Required Input
Do not proceed without one of:
- Full issue URL (
https://github.com/{owner}/{repo}/issues/{number}), or - Owner/repo plus issue number (
{owner}/{repo}#{number})
If neither is available, ask for it first.
Persistence Contract (Managed Comment)
Persist the plan in one managed issue comment with a stable marker:
<!-- agentic:github-issue-plan -->
Rules:
- Exactly one managed comment per issue per planning thread.
- Update that managed comment in place on subsequent runs (idempotent).
- Keep the marker at the top of the comment body so it is discoverable.
- Use
issue-comment-template.mdas the body scaffold.
Decision Tree
- MCP path (preferred):
- If GitHub MCP is available and configured, use MCP issue/comment tools to find
existing comments containing
<!-- agentic:github-issue-plan -->and update. - Enforce deterministic managed-comment handling:
- 0 matching comments: create one managed comment with marker + plan body.
- 1 matching comment: update that exact managed comment.
- More than 1 matching comment: stop and request manual cleanup before updating.
ghCLI fallback (primary fallback, not hard-block):
- If MCP is unavailable or misconfigured, continue using
ghCLI. - Check auth first:
gh auth status
- Create a managed comment:
gh issue comment {issue_number} --repo {owner}/{repo} --body-file /tmp/issue-plan.md
- Update existing managed comment (find exactly one comment id, then edit):
MATCHED_IDS=$(gh api repos/{owner}/{repo}/issues/{issue_number}/comments --paginate \
--jq '.[] | select(.body | contains("<!-- agentic:github-issue-plan -->")) | .id')
MATCH_COUNT=$(printf "%s\n" "$MATCHED_IDS" | sed '/^$/d' | wc -l | tr -d ' ')
if [ "$MATCH_COUNT" -gt 1 ]; then
echo "Multiple managed plan comments found; stop and ask for manual cleanup."
exit 1
fi
COMMENT_ID=$(printf "%s\n" "$MATCHED_IDS" | sed '/^$/d' | head -n 1)
gh api repos/{owner}/{repo}/issues/comments/$COMMENT_ID \
--method PATCH \
--field body="$(cat /tmp/issue-plan.md)"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 107 lines · 62 tokens per session scan A 159145d1197c
github-issue-planning is a skill published in the GitHub repository soulcodex/agentic (10 stars, last pushed 2d ago), licensed MIT. It adds 62 tokens to every session and 827 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 2026-08-31.
Other skills, from other repositories
github-multi-repo
Multi-repository coordination, synchronization, and architecture management across many GitHub repos. Use when changes span several repositories, keeping repos in sync, or planning cross-repo architecture and dependency work.
issue-triage
Issue triage: audit open issues, categorize, detect duplicates, cross-ref PRs, risk assessment, post comments. Args: "all" for deep analysis of all, issue numbers to focus (e.g. "42 57"), "en"/"fr" for language, no arg = audit only in French.
design-debt-audit
Inventory and prioritise accumulated design inconsistencies across a product. Use when drift has built up over time. For token coverage specifically use design-token-audit (designer-toolkit); for WCAG gaps use accessibility-audit (design-systems).
design-impact-reporting
Communicate design's contribution to business and user outcomes in stakeholder language. Use when reporting results upward. For choosing the metrics in the first place, use metrics-definition (ux-strategy).
research-repository
Build a repository that makes findings findable, reusable, and cumulative across teams. Use when the same research keeps getting redone. For synthesising one study, use affinity-diagram.
survey-design
Design unbiased survey instruments — question wording, scales, and sampling — to measure attitudes at scale. Use when you need quantitative breadth. For behavioural experiments, use a-b-test-design (prototyping-testing).