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/e1024kb/wise-claude/wise-implement-plan-autonpx skills add e1024kb/wise-claude --skill wise-implement-plan-autogit clone --depth 1 https://github.com/e1024kb/wise-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/e1024kb/wise-claude/wise-implement-plan-auto)<a href="https://agentmods.dev/skills/e1024kb/wise-claude/wise-implement-plan-auto"><img src="https://agentmods.dev/badge/skills/e1024kb/wise-claude/wise-implement-plan-auto.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00147 | $0.00913 |
| Opus 5 | $0.00073 | $0.00456 |
| Sonnet 5 | $0.00029 | $0.00183 |
| Haiku 4.5 | $0.00015 | $0.00091 |
Grade A, and why
wise-implement-plan-auto 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 4d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/wise-implement-plan-auto — execute a plan, autonomously
Why this skill exists
ticket-plan and ticket-auto produce a PLAN-*.md but no skill
executes one. /wise-implement-plan-auto is that executor — a
phase-gated model: parse the plan's task waves, dispatch one fresh-context
executor agent per task in parallel, commit each task atomically,
verify as it goes. It is the reusable building block the ticket-auto
workflow's implement phase follows.
Arguments
Read $ARGUMENTS. The first whitespace-separated token, if present,
is the path to the PLAN-*.md to implement. When absent, look for a
single PLAN-*.md at the git toplevel and use it; if there are zero
or several, stop and ask the user to name one.
Procedure
1. Resolve the worktree + plan
git rev-parse --show-toplevel
Use the toplevel as worktree. Resolve plan_path from $ARGUMENTS
(or the discovery rule above).
2. Follow the shared fragment
Read ${CLAUDE_PLUGIN_ROOT}/workflows/ticket-auto/prompts/implement-plan.md
and follow it end to end with plan_path, worktree, project.kind
(infer from the worktree's manifest if unknown), and SUPERVISE=yes.
The fragment processes waves in order, dispatches the wave's executors
per task (persona: this skill's agents/executor.md) — supervised
background teammates a leader loop nudges if one hangs or goes idle
mid-task — then simplifies (per-task, scoped to the task's files via
references/simplify-pass.md) and commits each task sequentially, and
verifies per task. (To fall back to plain blocking Task executors,
pass SUPERVISE=no / set WISE_WORKER_* env to tune the watchdog.)
3. Relay the result
The fragment's final line is
IMPLEMENT: waves=<w> tasks=<t> done=<d> failed=<f>. Summarise for
the user — waves run, tasks done, tasks failed (with which ones) —
and remind them nothing was pushed (commit/push is a separate step).
Guardrails
- Never call
AskUserQuestionmid-run — the only prompt is the argument-resolution stop in §Arguments when the plan is ambiguous. - One atomic commit per task; never bundle tasks.
- Executors edit files; only this skill simplifies (per-task, scoped) and commits, serially — never let parallel subagents race the git index. The heavier high-depth code-review branch gate is a separate, later pipeline step, not this skill's job.
- Never
git push— that is the caller's step. - A failed task does not abort the run.
- Never invoke another wise action skill.
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.
- 4d ago First seen · 79 lines · 147 tokens per session scan A fdca4ed5c739
wise-implement-plan-auto is a skill published in the GitHub repository e1024kb/wise-claude (4 stars, last pushed 9d ago), licensed MIT. It adds 147 tokens to every session and 913 once invoked, about $0.0007 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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