mindit-trace

mindit-trace is a skill for Claude Code, Codex from Dragoon0x/usemindit. It costs 125 tokens per session (1,524 once invoked), scanned A, original, MIT.

A tool for tracing design decisions recorded in `.mindit/decisions/`, including their supporting evidence and related decisions.

In plain words
What is it for?
Use it to investigate decision history, follow dependencies, prepare for changes, onboard teammates, or review past evidence.
Why use it?
It helps explain why a technical choice was made and what other choices or systems depend on it.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/dragoon0x/usemindit/mindit-trace
Any agent
npx skills add Dragoon0x/usemindit --skill mindit-trace
Clone the repo
git clone --depth 1 https://github.com/Dragoon0x/usemindit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for mindit-trace

README.md
[![agentmods](https://agentmods.dev/badge/skills/dragoon0x/usemindit/mindit-trace.svg)](https://agentmods.dev/skills/dragoon0x/usemindit/mindit-trace)
Your own site
<a href="https://agentmods.dev/skills/dragoon0x/usemindit/mindit-trace"><img src="https://agentmods.dev/badge/skills/dragoon0x/usemindit/mindit-trace.svg" alt="Measured on agentmods" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,524 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00125 $0.01524
Opus 5 $0.00063 $0.00762
Sonnet 5 $0.00025 $0.00305
Haiku 4.5 $0.00013 $0.00152

Measured 3d ago against content hash e427e739a353, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mindit-trace 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 3d 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.

skills/mindit-trace/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

mindit-trace

The third of three meta skills. Run this when the question is "how did we get here, and what depends on this."

What this skill does

Reads the decision artifacts already stored in .mindit/decisions/ and walks the graph defined by depends_on references. Surfaces the chain of reasoning behind a current design state. Lets the team answer "why did we decide X" by looking at the actual artifacts produced when X was decided, including the evidence cited at the time.

This is what mindit's stateful, file-based architecture exists for. Layers-style pure-prose skills cannot do this; mindit can.

When to run this

  • The user asks "why did we decide X," "what was the reasoning behind Y."
  • The user is about to change a decision and wants to know what else depends on it.
  • The user is onboarding a new team member and wants to walk them through how the design got to its current state.
  • The user is doing a retrospective and wants to revisit the evidence that backed prior decisions.
  • The user asks for a "decision history," "decision chain," or "decision lineage."

How to analyze

  1. Locate the starting decision. The user names a decision by ID (e.g. clarity-20260311-checkout-cta) or by description ("the decision about the checkout CTA size"). If by description, search filenames and titles in .mindit/decisions/ to find the match. If multiple match, ask which one.

  2. Walk backward (dependencies). Read the depends_on field of the starting artifact. For each dependency, load that artifact, read its depends_on, recurse. Stop when you reach artifacts with no further dependencies (root decisions) or when you have walked five levels deep, whichever comes first.

  3. Walk forward (consequents). Grep the .mindit/decisions/ directory for artifacts whose depends_on includes the starting decision's ID. Recurse the same way.

  4. Build the trace. Produce both:

    • A backward chain: this decision was made because of X, which was made because of Y, which was made because of Z.
    • A forward chain: this decision is referenced by A, which is referenced by B.

Read the full file on GitHub · 121 lines

Changes

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.

  1. 3d ago First seen · 121 lines · 125 tokens per session scan A e427e739a353

Subscribe to this mod's changes

mindit-trace is a skill published in the GitHub repository Dragoon0x/usemindit (2 stars, last pushed 3mo ago), licensed MIT. It adds 125 tokens to every session and 1,524 once invoked, about $0.0006 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.

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