Borrowing it
Nothing to install: this file belongs to yuqie6/ProductFlow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yuqie6/ProductFlow/main/.agents/skills/trellis-finish-work/SKILL.mdgit clone --depth 1 https://github.com/yuqie6/ProductFlowWrote 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/yuqie6/productflow/trellis-finish-work)<a href="https://agentmods.dev/skills/yuqie6/productflow/trellis-finish-work"><img src="https://agentmods.dev/badge/skills/yuqie6/productflow/trellis-finish-work/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/yuqie6/productflow/trellis-finish-work"><img src="https://agentmods.dev/badge/skills/yuqie6/productflow/trellis-finish-work.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 3 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
- high Data Exfiltration · line 8 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
- high Data Exfiltration · line 60 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
- medium Excessive Agency · line 45 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00046 | $0.00892 |
| Opus 5 | $0.00023 | $0.00446 |
| Sonnet 5 | $0.00009 | $0.00178 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
trellis-finish-work 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 11d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- trellis-finish-work — 100% identical, 6 lines differ
- trellis-finish-work — 100% identical, 6 lines differ
- trellis-finish-work — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finish Work
Wrap up the current session: archive the active task (and any other completed-but-unarchived tasks the user wants to clean up) and record the session journal. Code commits are NOT done here — those happen in workflow Phase 3.4 before you invoke this command.
Step 1: Survey current state
python3 ./.trellis/scripts/get_context.py --mode record
This prints:
- My active tasks — review whether any besides the current one are actually done (code merged, AC met) and should be archived this round.
- Git status — quick visual on what's dirty.
- Recent commits — you'll need their hashes in Step 4 for
--commit.
If --mode record surfaces other completed tasks not tied to the current session, surface them to the user with a one-shot confirmation: "These N tasks look done — archive them too in this round? [y/N]". Default is no; the current active task is always archived in Step 3 regardless.
Step 2: Sanity check — classify dirty paths
Run:
git status --porcelain
Filter out paths under .trellis/workspace/ and .trellis/tasks/ — those are managed by add_session.py and task.py archive auto-commits and will appear dirty as part of this skill's own work.
For each remaining dirty path, decide whether it belongs to the current task or to other parallel work (e.g., another terminal window editing the same repo). Heuristics:
- Paths referenced in the current task's
prd.md/implement.jsonl/check.jsonl→ current task - Paths in code areas matching the task's stated scope, or that you remember editing this session → current task
- Paths in unrelated areas you have no recollection of touching this session → other parallel work
Then route:
-
Any remaining path looks like current-task work — bail out with:
"Working tree has uncommitted code changes from this task:
<list>. Return to workflow Phase 3.4 to commit them before running ``finish-work(Trellis command)."Do NOT run
git commithere. Do NOT prompt the user to commit. The user goes back to Phase 3.4 and the AI drives the batched commit there. -
All remaining paths look unrelated (other parallel-window work) — report them once and continue to Step 3:
"FYI, dirty files outside this task's scope — leaving them for the other window:
<list>." -
Genuinely unsure — ask the user once: "Are
<list>this task's work I forgot to commit, or another window's? (commit / ignore)" — then route per their answer.
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.
- 11d ago First seen · 72 lines · 46 tokens per session scan A 161060fbcd44
trellis-finish-work is a skill published in the GitHub repository yuqie6/ProductFlow (302 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 892 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 2026-08-30.
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