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 commands/rajconnects/founder-stack/grillgit clone --depth 1 https://github.com/rajconnects/founder-stackWhat 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 | $0.00054 | $0.01187 |
| Opus 5 | $0.00027 | $0.00593 |
| Sonnet 5 | $0.00011 | $0.00237 |
| Haiku 4.5 | $0.00005 | $0.00119 |
Grade A, and why
grill 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 yesterday.
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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running a grilling session: stress-testing a plan against the project's documented thinking before it advances to implementation.
Arguments: $ARGUMENTS
Steps
-
Resolve the plan to grill.
- If
$ARGUMENTSis a file path, read it. - If
$ARGUMENTSiscurrentor empty, use the active plan-mode plan from this conversation. - If neither, ask the user: "Which plan should I grill? Paste it, give me a path, or say
currentto use the in-conversation plan."
- If
-
Resolve project context. Read
.claude/project.json. Extract:context_doc— the project's primary thesis/context document (e.g.CLAUDE.md,CONTEXT.md).glossary_doc+glossary_anchor— where the project's domain vocabulary lives.decision_records.pathanddecision_records.format— where prior resolved decisions are stored.architecture_notes— where long-form architecture memos live (optional).
-
Load the project's thinking. Read in this order:
- The
context_docin full. - The glossary section (anchor) inside
glossary_doc. - Index decision records:
- If
formatisjson-traces: glob<path>/*.json, read each, build a list of(topic, status, resolution_summary, revisit_trigger)tuples. Filter tostatus: resolvedfor the challenge phase. - If
formatismarkdown-adr: glob<path>/*.md, parse the title and "Decision" / "Consequences" sections. - If
formatismixed: do both.
- If
- Skim
architecture_notesfilenames for any obviously relevant memos. Read full content only if a name matches the plan's scope.
- The
-
Run the grilling loop. Walk down each branch of the plan's decision tree, one question at a time. For each question, also propose your recommended answer based on what you've read. Wait for the user's response before continuing to the next question. Stop only when every branch is resolved or explicitly deferred.
Cover at minimum:
- Glossary conflicts. Does the plan use a term that conflicts with the glossary's definition? Surface it: "The glossary says X means A, but you seem to mean B — which is it?"
- Fuzzy terms. Does the plan use vague or overloaded words? Propose a precise canonical term from the glossary.
- Prior decision conflicts. Does the plan contradict any resolved decision record? Surface the trace ID and the original resolution. Ask: "This conflicts with [trace topic, resolved on date]. The original resolution was: [summary]. Reopen, or revise the plan?"
- Concrete scenarios. When the plan asserts how something works, invent a concrete edge-case scenario and ask the user to confirm. ("If a user does X mid-flow, what does the plan say happens?")
- Untested assumptions. When the plan asserts a fact, ask: "How do we know this? Is there a measurement, a prior decision, or is this assumption?" Tag assumptions for later validation.
- Code agreement. When the plan describes how the system behaves, spot-check the code if a path is implied. Surface any divergence between plan and code.
-
Update the project's thinking inline. As terms are resolved or decisions crystallize, do not batch them.
- Glossary update needed. If the user clarifies or introduces a term that should live in the glossary, propose the exact diff and ask permission before writing.
- Decision needs capturing. If the grilling produces a new decision (or revises a prior one), say: "This is decision-worthy — want me to capture it via the existing decision-trace flow?" Hand off to whatever the project's decision-capture skill is (do not fabricate one). If the project ships with a
decision-trace-captureskill, that's typically what/handoffinvokes.
-
Print a session summary. When the user signals "done":
- Number of branches grilled.
- Number of glossary updates proposed (and accepted).
- Number of decision-record conflicts surfaced.
- Number of new decisions worth capturing.
- Plan status: ready to advance to plan-mode approval / needs revision / blocked.
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.
- yesterday First seen · 60 lines · 54 tokens per session scan A 5c3a0b63f7b5
grill is a command published in the GitHub repository rajconnects/founder-stack (2 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 1,187 once invoked, about $0.0003 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.