iflow-cycle

A skill for processing a queue of software issues one after another, using an automated issue workflow for each one.

In plain words
What is it for?
Use it with issue numbers, a label, an epic stage, or a saved resume state. It can run the workflow through planning, implementation, closing, pull-request merging, and returning to the default branch.
Why use it?
It removes the need to start and finish each small issue manually, but is intended only for issues that are clearly specified, low risk, and covered by tests.

Skill for Claude CodeCodexCursor

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/jepegit/issue-flow/iflow-cycle
Any agent
npx skills add jepegit/issue-flow --skill iflow-cycle
Clone the repo
git clone --depth 1 https://github.com/jepegit/issue-flow

Made for: Claude Code, Codex, Cursor.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,216 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 $0.00039 $0.03216
Opus 5 $0.00019 $0.01608
Sonnet 5 $0.00008 $0.00643
Haiku 4.5 $0.00004 $0.00322

Measured 2d ago against content hash b2e3da415e6a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

iflow-cycle 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.

.cursor/skills/iflow-cycle/SKILL.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

issue-flow — issue cycle (/iflow-cycle)

Follow this skill to process a queue of issues hands-off, one after another, with a single up-front confirmation — the batch equivalent of /iflow-yolo. Each issue runs the full yolo chain (init → plan → build → close yolo, PR auto-merged, switch back to default); the cycle interrupts you only when input is strictly necessary.

Use only when every queued issue is genuinely yolo-fit (small, low-risk, well-specified, test-guarded). A queue of risky changes belongs in the individual commands.

Input — queue spec

  • explicit numbers — e.g. 12 15 18.
  • yolo — alias for label:yolo: every open issue carrying the configured yolo trigger label (default "yolo"). Case-insensitive. This is the one-token path for “auto-process all yolo issues.”
  • label:<L> — every open issue carrying label <L> (use for labels other than the yolo trigger).
  • epic <N> [stage <k>] — the current stage of epic <N> (or stage <k>).
  • resume — pick up an interrupted cycle from its state file (see Resuming below).
  • onfail:stop (default) / onfail:skip — failure policy (see step 7).
  • max:<n> — raise the safety cap (default 10) for this run.
  • stay — forward stay to each close so the working copy stays on each issue branch (rarely wanted in a cycle).

Invoke: type iflow cycle in chat, or /iflow-cycle from the slash menu (iflow-cycle also works).

MODEL & EXECUTION DIRECTIVE

Profile: reasoning — Prioritize deep thinking and careful trade-offs over speed or token economy.

In Cursor: switch to a thinking-capable model before invoking this step (not Auto-only).

Keep scope tight to what this step requires.

Resolve project root (multi-root workspaces)

Before any git, gh, or .issueflows/ path operation in this workflow:

Resolution order (stop when unambiguous):

  1. Explicit hints in slash input — root:<path>, repo:<folder-basename> (directory name, e.g. cellpy-core), or repo:owner/name.
  2. CLI fast pathissue-flow agent resolve [-C <start>] [--from-file <active-file>] [--json]. Use the returned project_root and repo; pass -C <project_root> to other issue-flow agent … subcommands. When the answer came from the workspace registry, the payload sets resolved_via_workspace_default: true.
  3. Branch context — exactly one workspace repo whose branch matches ^\d+- → that root.
  4. Single scaffold — exactly one .issueflows/ tree visible in the workspace → that root.
  5. Workspace default — an issueflow-workspace.toml at the workspace root (created with issue-flow workspace init) may name a default member repo; use it when no scaffold matched above. Tell the user the default was used.
  6. Ambiguousstop and ask; never guess between sibling repos.

Read the full file on GitHub · 148 lines

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 · 148 lines · 39 tokens per session scan A b2e3da415e6a

Subscribe to this mod's changes

iflow-cycle is a skill published in the GitHub repository jepegit/issue-flow (4 stars, last pushed 20d ago), licensed MIT. It adds 39 tokens to every session and 3,216 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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