GSD Pi is a command-line coding agent and project workflow system that plans, implements, verifies, and tracks software work through milestones, tasks, Git worktrees, and stored project notes. It is for developers who want structured, longer-running agent sessions using different model providers. The catalogue entries extend GSD Pi with skills and agents.
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 open-gsd/gsd-pi --skill grill-megit clone --depth 1 https://github.com/open-gsd/gsd-piWrote 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/open-gsd/gsd-pi/grill-me)<a href="https://agentmods.dev/skills/open-gsd/gsd-pi/grill-me"><img src="https://agentmods.dev/badge/skills/open-gsd/gsd-pi/grill-me/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/open-gsd/gsd-pi/grill-me"><img src="https://agentmods.dev/badge/skills/open-gsd/gsd-pi/grill-me.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 | $0.00091 | $0.01185 |
| Opus 5 | $0.00046 | $0.00593 |
| Sonnet 5 | $0.00018 | $0.00237 |
| Haiku 4.5 | $0.00009 | $0.00119 |
Grade A, and why
grill-me 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 10d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this skill when:
- The user asks to be grilled, stress-tested, or interrogated
- A plan reads like a list of happy paths with no failure modes
- Two or more sections of a plan implicitly depend on one undecided choice
- The user says "I think" or "probably" about something that will bind the design
<core_principle> ONE QUESTION AT A TIME. Parallel questions destroy dependency order — the answer to Q2 is often contingent on the answer to Q1, and asking both at once forces the user to reason about a combinatoric space instead of a single fork. Ask, wait, absorb, ask the next.
RECOMMEND AN ANSWER. Every question ships with your recommendation and a one-line reason. The user's job is to confirm, override, or redirect — not to generate answers from scratch.
CODEBASE BEFORE QUESTION. If the answer exists in the repo — a convention, an existing pattern, a prior decision — find it and cite it rather than asking. </core_principle>
Step 1: Map the decision tree silently
Before asking anything, read what the user has already said in this conversation plus any existing M###-CONTEXT.md, S##-CONTEXT.md, and .gsd/DECISIONS.md. Build a private list of every decision the plan depends on, in dependency order. Do not show this list — it is scaffolding.
If the plan touches unfamiliar code, spawn Agent(subagent_type=Explore) in parallel to map the relevant modules while you prepare Question 1. Do not wait for it to finish before starting the interview.
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.
- 10d ago First seen · 94 lines · 91 tokens per session scan A 8e819764e8ab
grill-me is a skill published in the GitHub repository open-gsd/gsd-pi (1,214 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 1,185 once invoked, about $0.0005 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.
Other skills, from other repositories
gsd-graphify
Build, query, and inspect the project knowledge graph in .planning/graphs/.
gsd-mempalace-capture
File a phase artifact into MemPalace; mirror decision facts into its temporal KG.
gsd-mempalace-recall
Recall decisions, patterns, and surprises from MemPalace before planning.
gsd-quick
Execute a quick task with GSD guarantees (atomic commits, state tracking) but skip optional agents.
gsd-surface
Toggle which skills are surfaced — apply a profile, list, or disable a cluster without reinstall.
gsd-complete-milestone
Archive completed milestone and prepare for next version.