feature-loop

A session workflow for coding agents that handles one project feature at a time, checks the work, and leaves the code ready to merge.

In plain words
What is it for?
Use it to select the next eligible feature, implement it through defined coding phases, run the project’s checks, and maintain a mergeable branch.
Why use it?
It prevents several unfinished features from being worked on together and requires verification before a feature is marked 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/demondamon/agenticx/feature-loop
Any agent
npx skills add DemonDamon/AgenticX --skill feature-loop
Clone the repo
git clone --depth 1 https://github.com/DemonDamon/AgenticX

Made for: Claude Code, Codex.

Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 763 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 $0.00024 $0.00763
Opus 5 $0.00012 $0.00381
Sonnet 5 $0.00005 $0.00153
Haiku 4.5 $0.00002 $0.00076

Measured 2d ago against content hash b60149821ba2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature-loop 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

agenticx/skills/bundled/feature-loop/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Loop

Use when session_mode == feature_loop and the project is past the Initializer phase (system prompt will say "Coding 阶段").

Iron rules

  1. One feature per session. Multiple in_progress features are forbidden by the store; do not bypass.
  2. Always verify before commit. feature_complete rejects features that have not been promoted to verified via verify_run.
  3. Keep the branch mergeable. Each commit must compile, pass verify.yaml, and not depend on uncommitted local state.

Loop

  1. Sync from disk. Call project_status first thing every session — it reads feature_list.json / status.json / progress.md and reseeds your understanding from the single source of truth.
  2. Pick a feature.
    • If status.active_feature_id is already set, resume that one (the prompt block will tell you).
    • Otherwise call feature_select with no arguments to auto-pick the highest-priority pending feature with satisfied dependencies, or pass feature_id when the user names one.
  3. Implement using code_dev phases (Explore → Read → Author):
    • Explore with code_outline, grep, optional code_search.
    • Read with file_read slices (start/end line). Track files you have read in scratchpad.
    • Author with file_write skeletons first, then section-by-section appends.
  4. Run the gate. Call verify_run feature_id=<id>. If any step fails:
    • Do not call feature_complete.
    • Log a progress_append with the failing step name and root cause.
    • Decide: fix and rerun verify_run, or escalate to the user with the specific failure.
  5. Commit via shell.
    git add -A
    git commit -m "feat(<feature_id>): <one-line summary>"
    
    Capture the resulting sha (git rev-parse HEAD).
  6. Promote to committed. Call feature_complete feature_id=<id> commit_sha=<sha>. The store writes an immutable archive snapshot under .agx/project/archive/feature_<id>.json.
  7. Decide next step. Either call feature_select for the next feature in the same session, or stop and tell the user the loop closed cleanly.

Read the full file on GitHub · 61 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 · 61 lines · 24 tokens per session scan A b60149821ba2

Subscribe to this mod's changes

feature-loop is a skill published in the GitHub repository DemonDamon/AgenticX (219 stars, last pushed 2d ago), licensed Apache-2.0. It adds 24 tokens to every session and 763 once invoked, about $0.0001 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.