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/nicoladevera/thinking-stack/convictiongit clone --depth 1 https://github.com/nicoladevera/thinking-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 | $0.00021 | $0.01654 |
| Opus 5 | $0.00010 | $0.00827 |
| Sonnet 5 | $0.00004 | $0.00331 |
| Haiku 4.5 | $0.00002 | $0.00165 |
Grade A, and why
conviction 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conviction — Epistemic Belief Audit
You are running a conviction audit: a structured epistemic analysis that takes a belief, claim, or decision in $ARGUMENTS and turns it into a falsifiable scorecard — mapping assumptions, weighing evidence, scoring confidence, and designing the cheapest test that could prove you wrong.
The user invoked this with: $ARGUMENTS
Phase 1: Intake & Readiness
Assess whether $ARGUMENTS contains a clear belief or claim. You need: (1) a stated belief, claim, or decision, and (2) enough context to reason about what would make it true or false.
If the input is too thin (no discernible claim, purely emotional, no domain context):
Use AskUserQuestion to ask up to 3 targeted clarifying questions. Only ask what's actually missing:
- What is the belief or claim you're trying to evaluate?
- What domain or context does this apply to? (e.g., your team, a product, a market, a personal decision)
- What are the stakes or time window, if relevant? (low/medium/high — helps calibrate how much rigor to apply)
If the input is ready: proceed directly.
Once you have enough context, restate the claim in falsifiable form — a precise statement that could, in principle, be shown to be true or false. Surface it before proceeding (no confirmation required — just present it and move on):
Claim (falsifiable): [Precise, falsifiable restatement of the belief]
Phase 2: Research (Optional, Targeted)
Determine whether external data would meaningfully ground the analysis: base rates, analogous comparisons, published benchmarks, or documented evidence relevant to the claim.
If yes: run 2–3 targeted WebSearch / WebFetch queries. Surface relevant findings in a brief paragraph before the audit. Focus on:
- Empirical data or benchmarks directly bearing on the claim
- Analogous cases where similar beliefs were tested and what the outcome was
- Known base rates for the domain (e.g., adoption rates, failure rates, performance benchmarks)
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 · 178 lines · 21 tokens per session scan A 9060db86cd2f
conviction is a command published in the GitHub repository nicoladevera/thinking-stack (2 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,654 once invoked, about $0.0001 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
change
Entry point for any change request. Orchestrates the planner-routing pipeline (cm-planner → executor → reviewer → conventions-audit → test-author → commit). Use for any work that touches code or docs.
tree
Show file tree with sync status indicators showing which files are indexed, modified, new, or deleted.
adr
You are helping create a new ADR (Architecture Decision Record). This is a conversational process — you interview the user about the decision, then create a filled-in record. ADRs capture the WHY behind technical choices so future-you understands the reasoning.
routine
Execute one maintenance routine defined in scv/routines/ .md (task + guardrails + exit-criteria contract), or list defined routines. SCV never schedules — pair with host features like /loop or cron yourself. Use whenever the user asks to run a recurring maintenance task, or asks what routines exist — not only when…
tldr
Re-apply TLDR rules for this turn (verdict first, no filler).
guide
Interactive guide to fellowship. Walks you through a real task using the structured research-plan-implement flow, then shows you what's next.