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 skills add MiaoDX/intuitive-flow --skill intuitive-port-worktreegit clone --depth 1 https://github.com/MiaoDX/intuitive-flowWrote 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/miaodx/intuitive-flow/intuitive-port-worktree)<a href="https://agentmods.dev/skills/miaodx/intuitive-flow/intuitive-port-worktree"><img src="https://agentmods.dev/badge/skills/miaodx/intuitive-flow/intuitive-port-worktree/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/miaodx/intuitive-flow/intuitive-port-worktree"><img src="https://agentmods.dev/badge/skills/miaodx/intuitive-flow/intuitive-port-worktree.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00025 | $0.00540 |
| Opus 5.5 | $0.00010 | $0.00216 |
| Sonnet 5.5 | $0.00005 | $0.00108 |
| Haiku 4.5 | $0.00003 | $0.00054 |
Grade A, and why
intuitive-port-worktree 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 1mo 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intuitive Port Worktree
Port selected commits or patches into the target checkout's current branch. Do not switch it to the source branch. Resolve source, target, and payload from the request; ask only if ambiguity risks moving the wrong work.
Inspect target status before editing, preserve unrelated changes, and stop for unclear overlapping edits. Create a backup-before-port- branch before applying. Never use destructive cleanup or remove remote folders.
Read application to select the payload and choose cherry-pick, patch, or manual reconstruction. Resolve mechanical drift while preserving intent; ask when source/target differences require a new contract, private-data, safety, or scope decision.
Verification
After applying changes:
Run git diff --stat, git diff --check, and git status --short in the
target.
Run the smallest relevant project verification. Prefer repo-native commands
from docs, Makefile, or AGENTS.md. If the target is a Python worktree that uses
activate.sh, uv_run.sh, or make, use those rather than bare uv run.
If the source operation had known runtime evidence, rerun or cite the closest target-side equivalent. Do not mark complete without some verification signal.
Commit Policy
Auto-commit successful ports by default after verification passes when there was no semantically large conflict. The user asked for a port, so the normal complete state is a focused target commit, not merely staged changes.
Use one focused commit in the target. The message should describe the result, not the transport mechanism, unless the port itself is the point.
Do not auto-commit when:
- verification failed or was skipped for reasons that make the port unsafe to claim complete;
- the target had overlapping local changes or unrelated staged changes that could be swept into the commit;
- the port required a semantically large decision as defined above;
- the user explicitly asked not to commit.
What ships with it
3 files 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.
- 1mo ago Changed · -176 lines · -54 tokens per session eefd0f8c8200
- 1mo ago First seen · 237 lines · 79 tokens per session scan A 5cbd7e7c1107
intuitive-port-worktree is a skill published in the GitHub repository MiaoDX/intuitive-flow (48 stars, last pushed 9d ago), licensed MIT. It adds 25 tokens to every session and 540 once invoked, about $0.0001 per session on Opus 5.5. 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.
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Investigate GitHub repository history before risky code changes using git blame/log, GitHub PRs, review comments, squash/rebase/cherry-pick/rename heuristics, and cited evidence. Use when asking why code exists, whether a change is safe, what PR introduced behavior, or before editing API, compatibility, security…
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Use when development work is complete and you need to prepare for merge. Guides through cleanup, testing, documentation, and creating a well-structured pull request.
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit…
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Merge PR, wait for CI, verify deploy, run canary. The complete landing pipeline.