Agent skill

Thinking Systems

by tjboudreaux in tjboudreaux/cc-thinking-skills

When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

MITAuto-check passed

Install Thinking Systems

skills CLI
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-systems -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install tjboudreaux/cc-thinking-skills thinking-systems --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/tjboudreaux/cc-thinking-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/thinking-systems .claude/skills/thinking-systems && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
thinking-systems
GitHub stars
1.6k
Token cost
~1.1k tokens
SKILL.md length
497 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

  • Works in 7 steps: Bound the system. Name purpose, actors,… → Map stocks and flows. List accumulating… → Find feedback and delays. For each… → …
  • SKILL.md covers When to Use, When NOT to Use, Procedure and Output, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Thinking Systems is an agent skill from tjboudreaux/cc-thinking-skills. When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: 28 eval-informed mental models and critical-thinking skills for Claude Code, GitHub Copilot, Codex, Cursor, and other Agent Skills-compatible tools. The licence is MIT.

Example prompts

  • “/thinking-systems”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Bound the system. Name purpose, actors, boundary, and in/out flows. Exclude noise outside the decision horizon; include any path that can…
  2. Map stocks and flows. List accumulating stocks (queue depth, debt, cache size, WIP) and the rates that fill/drain them. Note what changes…
  3. Find feedback and delays. For each candidate loop: classify reinforcing (amplifies) vs balancing (resists); mark same-direction (+) vs…
  4. Match recurring structure when problems return. Check only if recurrence or policy resistance is present; do not force a pattern
  5. Trace symptom to structure. Walk upstream along flows and loops; separate proximate symptom from structural driver (interaction, delay…
  6. Rank interventions by leverage, then side effects. Prefer higher feasible class: goals/paradigm → rules/information → loop structure…
  7. Stop. Commit highest feasible intervention plus watch signals for loop/delay response. Re-map only if the structure changes or the…

What it can do on your machine

Read from SKILL.md and the folder at commit 7b8fece. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Thinking Systems loads about 1.1k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 497 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from tjboudreaux/cc-thinking-skills at commit 7b8fece, republished under its MIT licence (© tjboudreaux). 497 words, ~1,104 tokens.

Download SKILL.mdSave it as .claude/skills/thinking-systems/SKILL.md (or your agent's skills folder).
name
thinking-systems
description
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
disable-model-invocation
true

Systems Mapping and Leverage

Treat the problem as structure and interaction, not isolated parts. Map boundary, stocks/flows, loops/delays, and recurring patterns; intervene at the highest feasible leverage after a side-effect check.

When to Use

  • Symptom spans services/components; single-stack fixes fail or bounce.
  • A change in one place breaks another; behavior is emergent.
  • Problem recurs despite local fixes (structure, not only symptom).
  • Need to rank interventions when parameter/buffer tweaks do not stick.

When NOT to Use

  • Single-component linear bug with clear stack/diff—trace and fix.
  • Throughput limited by one obvious stage—use theory-of-constraints.
  • Decision is a consequence chain of one proposed action—use second-order.
  • Approach selection (plan vs probe vs stabilize)—use cynefin first.

Procedure

  1. Bound the system. Name purpose, actors, boundary, and in/out flows. Exclude noise outside the decision horizon; include any path that can feed the symptom.
  2. Map stocks and flows. List accumulating stocks (queue depth, debt, cache size, WIP) and the rates that fill/drain them. Note what changes slowly even when flows jump.
  3. Find feedback and delays. For each candidate loop: classify reinforcing (amplifies) vs balancing (resists); mark same-direction (+) vs opposite (-) links; name delays (TTL, deploy lag, metric lag, ramp-up). Even count of opposite links → reinforcing; odd → balancing. Long delay + strong correction → overshoot risk.
  4. Match recurring structure when problems return. Check only if recurrence or policy resistance is present; do not force a pattern:
    • Fixes That Fail — quick fix, delayed worse side effect
    • Shifting the Burden — workaround starves fundamental fix
    • Limits to Growth — growth hits a balancing constraint
    • Tragedy of the Commons — local optima deplete a shared stock
    • Escalation — mutual reaction spiral
    • Success to the Successful — advantage compounds via allocation
    • Growth and Underinvestment — capacity lags demand until crisis If none fits after a genuine pass, keep the from-scratch map.
  5. Trace symptom to structure. Walk upstream along flows and loops; separate proximate symptom from structural driver (interaction, delay, wrong goal, missing info).
  6. Rank interventions by leverage, then side effects. Prefer higher feasible class: goals/paradigm → rules/information → loop structure (gain, balancing add, delay shorten) → stock/flow topology → buffers/parameters. For each candidate: feasibility, blast radius, delayed reversal risk. Prefer moves that cut harmful reinforcing gain or strengthen needed balancing loops without creating a new commons/escalation.
  7. Stop. Commit highest feasible intervention plus watch signals for loop/delay response. Re-map only if the structure changes or the intervention fails its watch.
Show full SKILL.md (109 more words)Show less

Stop when boundary, key stocks/flows, dominant loop(s)+delay(s), optional archetype, and a ranked intervention with side-effect check are stated—or when the problem collapses to a single linear cause.

Output

text
boundary: <system purpose and edges>
stocks_flows: <stock → inflow/outflow list>
loops:
  - name: <loop>
    type: reinforcing | balancing
    delay: <where cause lags effect>
    links: <brief +/->
archetype: <name or none>
structural_driver: <one sentence>
interventions_ranked:
  - level: <goals|rules|loops|structure|params>
    action: <what>
    side_effects: <feedback/elsewhere/delay risk>
chosen: <highest feasible>
watch: <signals that confirm or falsify>

Verification

  • Falsify: If removing one component fully explains and fixes the issue with no cross-effects, systems mapping is wrong—drop to local debug. If utilization shows one fixed stage as the sole cap, switch to theory-of-constraints.
  • Stop: Do not keep adding loops after the chosen intervention and watch are set.
  • Over-application guard: No archetype without recurrence evidence. No low-leverage param tweak listed as primary when a feasible higher class exists. Do not recreate standalone archetype/feedback/leverage procedures—those checks live only inside this map.

© tjboudreaux, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/thinking-systems of tjboudreaux/cc-thinking-skills.

Open the folder on GitHubat commit 7b8fece

Compare with similar skills

Thinking Systems next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Thinking Systems compared with similar skills
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Thinking Systems this skilltjboudreaux/cc-thinking-skills1.6k—~1.1kAutomated safety check: PassMIT
Fixalirezarezvani/claude-skills28k1 repos~765Automated safety check: PassMIT
Fix Issuepytorch/pytorch104k—~2.3kAutomated safety check: PassCustom licence
Orch Fix Defectaffaan-m/ECC276k1 repos~414Automated safety check: PassMIT
Logic Fix Allsickn33/agentic-awesome-skills47k1 repos~1.3kAutomated safety check: PassMIT
Fixdavepoon/buildwithclaude3.6k—~14kAutomated safety check: NotesMIT

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Questions about Thinking Systems

What does Thinking Systems do?

When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage. Thinking Systems is an agent skill from tjboudreaux/cc-thinking-skills. When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

How do I install Thinking Systems in Claude Code?

Run `npx skills add tjboudreaux/cc-thinking-skills --skill thinking-systems -a claude-code`. Or copy the skill folder (skills/thinking-systems in tjboudreaux/cc-thinking-skills) into .claude/skills/thinking-systems in your project. Claude Code loads it when a task matches its description.

How do I install Thinking Systems in Codex?

Run `npx skills add tjboudreaux/cc-thinking-skills --skill thinking-systems -a codex`. Or copy the skill folder (skills/thinking-systems in tjboudreaux/cc-thinking-skills) into .agents/skills/thinking-systems in your project. Codex loads it when a task matches its description.

Can I use Thinking Systems in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tjboudreaux/cc-thinking-skills --skill thinking-systems -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/thinking-systems, .gemini/skills/thinking-systems, .github/skills/thinking-systems and .opencode/skills/thinking-systems in your project.

What does Thinking Systems need to run?

SKILL.md names no scripts, command-line tools or credentials: Thinking Systems is instructions for the agent only.

Does Thinking Systems access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Thinking Systems safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Thinking Systems use?

Thinking Systems is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Thinking Systems use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Thinking Systems?

Skills that share tags, products or a category with Thinking Systems: Fix (alirezarezvani/claude-skills, 28k stars), Fix Issue (pytorch/pytorch, 104k stars), Orch Fix Defect (affaan-m/ECC, 276k stars) and Logic Fix All (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Thinking Systems?

tjboudreaux (a GitHub user) maintains it in tjboudreaux/cc-thinking-skills, which has 1,612 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on August 7, 2026.

Source: tjboudreaux/cc-thinking-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.