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/feo2x/guided-coding/guided-coding-prepare-issue-for-plannpx skills add feO2x/guided-coding --skill guided-coding-prepare-issue-for-plangit clone --depth 1 https://github.com/feO2x/guided-codingWhat 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 | $0.00035 | $0.00606 |
| Opus 5 | $0.00017 | $0.00303 |
| Sonnet 5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
guided-coding-prepare-issue-for-plan 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.
This is a copy
94% identical to prepare-issue-for-plan — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prepare an Issue for a Plan
Create the issue and branch only. Leave planning to the user and the planning conversation.
1. Check prerequisites
Read the repository instructions. Before creating the issue:
- Run
git status. If the worktree has uncommitted changes, stop before creating the issue. - Determine the repository's default branch.
- Determine the issue tracker and target project from repository instructions. If they are not
documented, infer them only when the git remote and tracker clearly agree, such as
ghwith a GitHub remote. State the inferred target and ask the user to confirm it. - When a tracker exists, confirm that its CLI is available and authenticated for the target project. Check its help rather than guessing flags.
Use the title supplied by the user. If none is provided, ask for a short title. Derive a lowercase, hyphen-separated topic of at most four words.
Example: Support cancelled events becomes cancelled-events.
2. Update the default branch
Switch to the default branch and update it before creating the external issue:
git switch <default-branch>
git pull --ff-only
Stop if either command fails.
3. Create the issue
Create the issue with the agreed title and an empty description. Do not add a summary, acceptance criteria, or placeholder text. Use the tracker's documented CLI. For GitHub:
gh issue create --title "<title>" --body ""
Read the identifier and URL from the command output. Normalize the identifier for filenames and
branches: convert it to lowercase, remove a leading #, replace each run of characters other than
a-z and 0-9 with one hyphen, trim leading and trailing hyphens, and do not add zero padding. Stop
if normalization produces an empty identifier.
If the project has no issue tracker, skip issue creation and use the topic alone for the branch and later plan filename.
4. Create the branch
Create <issue-id>-<topic> or, without an issue, <topic>. Validate the complete name before
creating it:
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.
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 · 74 lines · 35 tokens per session scan A 010ddadada93
guided-coding-prepare-issue-for-plan is a skill published in the GitHub repository feO2x/guided-coding (6 stars, last pushed 18d ago), licensed MIT. It adds 35 tokens to every session and 606 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to prepare-issue-for-plan, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.