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/jepegit/issue-flow/iflow-graphifynpx skills add jepegit/issue-flow --skill iflow-graphifygit clone --depth 1 https://github.com/jepegit/issue-flowWhat 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 | $0.00036 | $0.00989 |
| Opus 5 | $0.00018 | $0.00495 |
| Sonnet 5 | $0.00007 | $0.00198 |
| Haiku 4.5 | $0.00004 | $0.00099 |
Grade A, and why
iflow-graphify 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
issue-flow — graph rebuild (/iflow-graphify)
Follow this skill to refresh the project's graphify knowledge graph — a stale graphify-out/ after a large refactor, or the initial graph after installing graphifyy.
Do not use this skill from /iflow-build, /iflow-close, or /iflow. /iflow-graphify is opt-in only.
Invoke: type iflow graphify in chat, or /iflow-graphify from the slash menu (iflow-graphify also works).
MODEL & EXECUTION DIRECTIVE
Profile: economy — Prioritize speed and token economy over deep reasoning.
In Cursor: use Auto or a fast model before invoking this step.
Keep scope tight to what this step requires.
Instructions
-
Prefer
issue-flow graphifyfrom the project root:issue-flow graphifyWith no extra args this runs
graphify update <project>— AST-only, no LLM API key required, produces the fullgraphify-out/. To pick a different graphify subcommand, pass it as the first arg:issue-flow graphify extract(adds the slower semantic LLM pass for richer relationships — needs an API key),issue-flow graphify watch(live),issue-flow graphify cluster-only --no-viz, etc. Use-C <dir>to scan a project other than the current directory. Trailing flags pass through verbatim. Do not invent new wrapper flags. -
Fallback to
graphifydirectly whenissue-flowis unavailable:graphify update .graphifyis subcommand-based —graphify .on its own is not valid (graphify reportsunknown command '.'). Always pick a subcommand:updatefor the no-LLM AST build,extractfor the full semantic pass,watchfor a long-running watcher, etc. -
If graphify exits with "no LLM API key found", the user picked
extract(or another semantic subcommand) without configuring a backend. Cursor's own LLM is not available to subprocesses, so graphify cannot reuse it. Suggest one of:- Set an API key for
GEMINI_API_KEY/GOOGLE_API_KEY,ANTHROPIC_API_KEY,OPENAI_API_KEY, orMOONSHOT_API_KEY. - Run
issue-flow graphify extract --backend ollamato use a local LLM via Ollama (requires Ollama installed with a model pulled). - Drop the
extractarg and use the defaultissue-flow graphify(AST-only, no LLM).
- Set an API key for
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 · 80 lines · 36 tokens per session scan A 71e446e9a789
iflow-graphify is a skill published in the GitHub repository jepegit/issue-flow (4 stars, last pushed 19d ago), licensed MIT. It adds 36 tokens to every session and 989 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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