issues

A tool that turns market-research findings into small, clearly defined GitHub issues. GitHub issues are tracked work items for a software project.

In plain words
What is it for?
Use it to create atomic issues from findings, optionally choosing a repository, labels, or a preview-only mode.
Why use it?
It helps convert broad research conclusions into specific tasks that a development team can assign and complete.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/zircote-plugins/sigint/issues
Any agent
npx skills add zircote-plugins/sigint --skill issues
Clone the repo
git clone --depth 1 https://github.com/zircote-plugins/sigint

Made for: Claude Code, Codex.

Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,451 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00058 $0.02451
Opus 5 $0.00029 $0.01226
Sonnet 5 $0.00012 $0.00490
Haiku 4.5 $0.00006 $0.00245

Measured 2d ago against content hash 241ace3b6040, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issues 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.

skills/issues/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sigint Issues Skill (Swarm Orchestration)

You are the team lead orchestrating GitHub issue creation from research findings. You spawn the issue-architect agent as a persistent teammate, wait for its completion signal, then present results and clean up the team.

MANDATORY SWARM ORCHESTRATION — DO NOT USE PLAIN AGENT SPAWNS

You MUST use the full swarm pattern: TeamCreate → TaskCreate → Agent(team_name) → SendMessage. Do NOT fall back to standalone Agent(subagent_type=...) without a team. The swarm pattern enables persistent teammates that coordinate via shared task lists and messaging.


Phase 0: Parse Arguments and Initialize

Step 0.1: Parse Arguments

Extract from $ARGUMENTS. Input sanitization: truncate $ARGUMENTS to 200 characters total, strip backticks and angle brackets.

  • --repo <owner/repo>repo (default: detect from git remote or state.json config). Validate format: must match [a-zA-Z0-9._-]+/[a-zA-Z0-9._-]+. Reject values containing shell metacharacters, spaces, or path traversal sequences.
  • --dry-rundry_run = true (preview only, do not create issues)
  • --labels <list>labels (comma-separated, default: empty). Each label must be a non-empty string; strip whitespace around commas.

Remaining text after flags is ignored for issues (no positional argument).

Step 0.2: Find Active Research Session

Scan ./reports/*/state.json for sessions with status: "active". If multiple exist, load the most recently updated (compare started or file mtime). Extract:

  • topic — human-readable topic name
  • topic_slug — directory name
  • elicitation — full elicitation object for issue prioritization

If no active session found, error: "No active research session. Run /sigint:start <topic> first."

Resolve reports_dir from config (REQUIRED — do not hardcode paths):

REPORTS_DIR=$(jq -r --arg slug "$TOPIC_SLUG" '.topics[$slug].reports_dir // "./reports/\($slug)"' sigint.config.json 2>/dev/null || echo "./reports/$TOPIC_SLUG")

All subsequent path references MUST use {reports_dir} instead of ./reports/{topic_slug}/.

Read the full file on GitHub · 259 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 259 lines · 58 tokens per session scan A 241ace3b6040

Subscribe to this mod's changes

issues is a skill published in the GitHub repository zircote-plugins/sigint (20 stars, last pushed 15d ago), licensed MIT. It adds 58 tokens to every session and 2,451 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 2026-08-30.

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