Agent skill

Habit Words

by joetawil7 in joetawil7/first-pass

Learns the words a user habitually writes to their coding agent that make its answers worse ("be 100% sure", "don't assume", "full review", "are you sure?", "all fine, right?"), from what they…

MITAuto-check passedDevelopment

Install Habit Words

skills CLI
$ npx skills add joetawil7/first-pass --skill habit-words -a claude-code

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

GitHub CLI
$ gh skill install joetawil7/first-pass habit-words --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/joetawil7/first-pass.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/habit-words .claude/skills/habit-words && 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
habit-words
GitHub stars
98
Token cost
~1.7k tokens
SKILL.md length
917 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Learns the words a user habitually writes to their coding agent that make its answers worse ("be 100% sure", "don't assume", "full review", "are you sure?", "all fine, right?"), from what they…

  • Works in 6 steps: Read the sessions → Find the words → Map each word to checks → …
  • Review the users habit words
  • SKILL.md covers 1. Read the sessions, 2. Find the words, 3. Map each word to checks and 4. Show the user, plus 2 more sections
  • Calls node and claude

What it does

Habit Words is an agent skill from joetawil7/first-pass. Learns the words a user habitually writes to their coding agent that make its answers worse ("be 100% sure", "don't assume", "full review", "are you sure?", "all fine, right?"), from what they actually typed in their recent Claude Code sessions. Shows what each one does, what went wrong after it, and what to say instead, then writes the habit words block that maps each word to the checks it should trigger, so the checks run without the words. Use when asked to learn, read, refresh or review the user's habit words…

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. The repository describes itself as: Rules and checks that make Claude Code look around a change, not just at the lines it writes: ten questions before code, a reviewer that didn't write it, proof before done, bugs… The licence is MIT.

When your agent uses it

  • Review the users habit words
  • Which of my words make you worse
  • From setup-first-passs profile step
  • The start-of-session check says the habit words are due

Example prompts

  • “be 100% sure”
  • “t assume”
  • “full review”
  • “/habit-words”

Requirements

  • Pre-approved tools (allowed-tools): Read, Glob, Grep

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Read the sessions
  2. Find the words
  3. Map each word to checks
  4. Show the user
  5. Write the block
  6. Clean up

What it can do on your machine

Read from SKILL.md and the folder at commit ded5cdf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node
    • claude

    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

Habit Words loads about 1.7k tokens when it runs. Until then it costs about 170 tokens; SKILL.md has 917 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~170
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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 joetawil7/first-pass at commit ded5cdf, republished under its MIT licence (© joetawil7). 917 words, ~1,668 tokens.

Download SKILL.mdSave it as .claude/skills/habit-words/SKILL.md (or your agent's skills folder).
name
habit-words
description
Learns the words a user habitually writes to their coding agent that make its answers worse ("be 100% sure", "don't assume", "full review", "are you sure?", "all fine, right?"), from what they actually typed in their recent Claude Code sessions. Shows what each one does, what went wrong after it, and what to say instead, then writes the habit words block that maps each word to the checks it should trigger, so the checks run without the words. Use when asked to learn, read, refresh or review the user's habit words or prompts, "which of my words make you worse", from setup-first-pass's profile step, or when the start-of-session check says the habit words are due.
allowed-tools
Read, Glob, Grep

habit-words

"Be 100% sure" or "make it bug free" names no place to look, so it changes how sure the answer sounds, not what gets checked. This skill finds the words this user writes, from their own prompts, and maps each to the checks it should mean. The user never has to write them again, and when they do, the words trigger the checks instead of a more certain tone.

The block this skill writes follows ${CLAUDE_SKILL_DIR}/../setup-first-pass/assets/words-block.md: read it first, and keep its markers and shape.

1. Read the sessions

Plugin: node "${CLAUDE_SKILL_DIR}/../../scripts/cli.mjs" words reads the user's last 20 Claude Code sessions that hold a prompt they typed (--sessions <n> for another number), from ~/.claude/projects (or $CLAUDE_CONFIG_DIR/projects). It writes only what they typed to a temp file and prints the file's path, what it left out, the newest prompt's time, and how many prompts hit each phrase family. Left out: tool output, pasted text, notifications, messages from other sessions, skill and system text, commands, compaction summaries and turns a script started (claude -p). Prompts queued while the agent was busy are kept: they are often the corrections. The one thing kept that the user did not type is the end of the agent's reply before each prompt tagged "possible pushback". Anything that looks like a key, token, password, email or phone number is replaced: best effort, so never quote a line that still looks like one. Each run writes one new file; note every path.

Without the plugin (another tool), ask the user to paste 30 to 50 recent prompts, and work from those.

Say the coverage before the findings: sessions, dates, prompts, what was left out. Read the whole file. Past about 800 prompts, read every prompt the families or the pushback marker tag, plus a sample of 150 of the rest, and say so.

2. Find the words

  • The families are candidates, not verdicts. Keep a phrase where it asks for certainty or completeness without naming a check ("be 100% sure", "cover all cases"); drop it where it names one ("make sure the tests pass", "check if this is still true").
  • Find the user's own phrases the families miss, by reading: stacked demands ("dont assume, be 100% confident, cover all gaps" in one breath), yes-shaped questions, absolutes ("no hacking is possible"), frustration, open grants, and the ones that work well.
  • Count every phrase you report: node "${CLAUDE_SKILL_DIR}/../../scripts/cli.mjs" words --count "<regex>" (repeat --count for several; one read), with the same --sessions as step 1, so the counts cover the prompts you read. Every number shown comes from a count, never from reading. Prompts where the user talks about the words (like a request to run this skill) are counted too: say how many.
  • The impact: a prompt tagged "possible pushback" shows the end of the reply before it. A habit word followed, in the same session, by the user correcting the result ("reread your numbers", "that's wrong", "is it really working?") is the evidence. Quote at most a few words of a prompt, never a whole one, and never names, contacts, amounts or anything secret.
Show full SKILL.md (401 more words)Show less

3. Map each word to checks

For each word keep:

  • what the user writes, in their spelling;
  • how often (prompts, sessions), from a count;
  • what it does to an agent, in one line (why the answer gets worse, not better);
  • what happened after it, with the date, where the sessions show it;
  • the check it now triggers: the working rule that answers it, by its name (Evidence, the pre-mortem, Done means proven, Say the coverage, No yes by default, Pushback gets checked, Bugs: reproduce first, Grants stay narrow, One step at a time), or, when no rule covers it, one new instruction in the same style;
  • what to say instead: the words that name the check.

Also list the prompts that worked (they named the check, the source or the scope), so the user keeps them.

4. Show the user

A table: You wrote · How often · What it does · What happened · Say instead, the prompts that worked, then the block you will write. Ask before writing it.

5. Write the block

With a yes, write the block between its markers: the heading, one line saying the words mean the checks and never a more certain tone, and one bullet per word: "<the user's words>" (<n> prompts): <the check it triggers>. The start marker is

<!-- first-pass:words:start v<plugin version> through <newest prompt's time from step 1> from <n> sessions (written by the habit-words skill from the user's own prompts; re-run it to refresh) -->

The start-of-session check reads through to say when the words are due again: once 20 sessions the user typed in have changed since. If the user says "not now" to a refresh, set through in the existing marker to the current time and change nothing else.

Where: never in a file teammates share, because these are one person's words. So:

  • in a main folder, right after the profile block in the root AGENTS.md;
  • in a single repo, or wherever the profile block sits in a file the repo commits, in ~/.claude/CLAUDE.md instead;
  • an existing words block is replaced where it is, if that file is not shared; otherwise it is moved to ~/.claude/CLAUDE.md, and the report says so.

Never edit outside the markers.

6. Clean up

Delete every file step 1 wrote (each words run writes one): they hold the user's prompts. node "${CLAUDE_SKILL_DIR}/../../scripts/cli.mjs" words --delete "<file>" for each; it fails if the name matches no file, so a mistyped name never reads as deleted. A file an unfinished run left is removed by the next run once it is 6 hours old. The report ends with:

Read: <n> prompts from <n> sessions, <first date> to <last date>; left out <what>
Words: <n> mapped (<n> new instructions), block <written to file | not written, because>
Temp files: <n> written, <n> deleted

© joetawil7, 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/habit-words of joetawil7/first-pass.

Open the folder on GitHubat commit ded5cdf

Compare with similar skills

Habit Words 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.

Habit Words compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Habit Words this skilljoetawil7/first-pass98—~1.7kAutomated safety check: PassMIT
Trellis Session Insightmindfold-ai/Trellis15k4 repos~1.7kAutomated safety check: PassAGPL-3.0
Warp Factory Fileswarpdotdev/warp65k1 repos~2.5kAutomated safety check: PassAGPL-3.0
Migrate Core Code to Submodulestinyhumansai/openhuman42k—~2.6kAutomated safety check: PassGPL-3.0
Analyze Logsactivepieces/activepieces25k1 repos~1.6kAutomated safety check: PassMIT
GitHub Review Iterationprisma/orm48k—~2.2kAutomated safety check: PassApache-2.0

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Questions about Habit Words

What does Habit Words do?

Learns the words a user habitually writes to their coding agent that make its answers worse ("be 100% sure", "don't assume", "full review", "are you sure?", "all fine, right?"), from what they…. Habit Words is an agent skill from joetawil7/first-pass."), from what they actually typed in their recent Claude Code sessions.

When should I use Habit Words?

Habit Words fits situations like: review the users habit words; which of my words make you worse; from setup-first-passs profile step; the start-of-session check says the habit words are due.

How do I install Habit Words in Claude Code?

Run `npx skills add joetawil7/first-pass --skill habit-words -a claude-code`. Or copy the skill folder (skills/habit-words in joetawil7/first-pass) into .claude/skills/habit-words in your project. Claude Code loads it when a task matches its description.

How do I install Habit Words in Codex?

Run `npx skills add joetawil7/first-pass --skill habit-words -a codex`. Or copy the skill folder (skills/habit-words in joetawil7/first-pass) into .agents/skills/habit-words in your project. Codex loads it when a task matches its description.

Can I use Habit Words 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 joetawil7/first-pass --skill habit-words -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/habit-words, .gemini/skills/habit-words, .github/skills/habit-words and .opencode/skills/habit-words in your project.

What does Habit Words need to run?

Going by SKILL.md and its folder, Habit Words needs the command-line tools its instructions call (node and claude). Its frontmatter pre-approves these tools: Read, Glob, Grep.

Does Habit Words 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 Habit Words 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 Habit Words use?

Habit Words 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 Habit Words use?

About 1.7k tokens (SKILL.md is roughly 6.7k 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 Habit Words?

Skills that share tags, products or a category with Habit Words: Trellis Session Insight (mindfold-ai/Trellis, 15k stars), Warp Factory Files (warpdotdev/warp, 65k stars), Migrate Core Code to Submodules (tinyhumansai/openhuman, 42k stars) and Analyze Logs (activepieces/activepieces, 25k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Habit Words?

joetawil7 (a GitHub user) maintains it in joetawil7/first-pass, which has 98 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 10, 2026.

Source: joetawil7/first-pass on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.