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/dentiny/kon/github-issue-summarynpx skills add dentiny/kon --skill github-issue-summarygit clone --depth 1 https://github.com/dentiny/konWhat 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 | $0.00037 | $0.00536 |
| Opus 5 | $0.00018 | $0.00268 |
| Sonnet 5 | $0.00007 | $0.00107 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
github-issue-summary 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 yesterday.
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.
What it actually says
GitHub Issue Summary
Owner: 📚 Jun (describe-issue mode)
Consumers: /kon:describe-issue
Core principles (always): follow skills/core-principles — first principles (don't hide the issue); simplest, most concise correct solution.
Orchestrator: gather context
gh issue view <N> --json title,body,state,labels,assignees,author,createdAt,updatedAt,comments,milestone,projectItems
For URLs: gh issue view https://github.com/owner/repo/issues/N --json ...
Include every comment (issue + review discussion). Pass full thread to Jun as ISSUE_CONTEXT. Set MODE: describe-issue and ISSUE_FILE: sessions/<SESSION_ID>/issue-summary.md.
If gh fails (no auth, wrong repo), ask the user for issue text or paste — do not hallucinate comments.
Write artifact
Jun must write structured markdown to ISSUE_FILE and reference that path in chat output.
Required file & output sections
In issue-summary.md and echoed in chat:
# Issue: <title>
**Number**: #N
**State**: open | closed
**Labels**: …
**Author / created**: …
## Issue summary
<What the issue asks for, in plain language — 2–5 sentences>
## Discussion summary
<Chronological or thematic summary of **all** comments — who said what, decisions, disagreements>
## Consensus / decisions
<What participants agreed on, or "(none yet)">
## Open questions
<Unresolved asks, blockers, or "(none)">
## Suggested next steps
<Concrete actions for implementer or PM — optional if issue is informational only>
Chat output must include:
## Loaded memory entries
...
## Issue summary
<one-line pointer>
Written summary to `<ISSUE_FILE>`.
Hard rules
- Read-only for application source — only write
issue-summary.md - No
gh issue closeor comment posting - Do not skip comments — summarize the full thread; if truncated by length, list omitted comment IDs/timestamps
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.
- yesterday First seen · 74 lines · 37 tokens per session scan A 33c76257a0b2
github-issue-summary is a skill published in the GitHub repository dentiny/kon (3 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 536 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 2026-08-31.
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