Intent Requirements Intake
Yeachan-Heo/oh-my-claudecode
Turns a pasted chat log or spoken problem report from support or ops staff into a reviewed five-section intent.md through numbered batches of questions.
A skill your agent uses when an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
MITAuto-check passed
Install Crystallize From Wal
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jianzhichun/emerge crystallize-from-wal --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/crystallize-from-wal .claude/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.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/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .claude/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-walType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jianzhichun/emerge crystallize-from-wal --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/crystallize-from-wal .agents/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .agents/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jianzhichun/emerge crystallize-from-wal --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/crystallize-from-wal .cursor/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .cursor/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jianzhichun/emerge.git --path skills/crystallize-from-wal--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jianzhichun/emerge crystallize-from-wal --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/crystallize-from-wal .gemini/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .gemini/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jianzhichun/emerge crystallize-from-walInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/crystallize-from-wal .github/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .github/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jianzhichun/emerge --skill crystallize-from-wal -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jianzhichun/emerge crystallize-from-wal --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianzhichun/emerge.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/crystallize-from-wal .opencode/skills/crystallize-from-wal && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "crystallize-from-wal" agent skill from https://github.com/jianzhichun/emerge/tree/main/skills/crystallize-from-wal into .opencode/skills/crystallize-from-wal/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "crystallize-from-wal", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
crystallize-from-wal- GitHub stars
- 104
- Token cost
- ~313 tokens
- SKILL.md length
- 149 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
- Works in 6 steps: Gather all successful WAL samples for… → Compare samples to separate constants… → Name parameters by domain meaning, using… → …
- An Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact
- SKILL.md covers Workflow, Rules and Output
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Crystallize From Wal is an agent skill from jianzhichun/emerge. Use when an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
Its SKILL.md is about 310 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The licence is MIT.
When your agent uses it
- An Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact
Example prompts
- “/crystallize-from-wal”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Gather all successful WAL samples for the intent.
- Compare samples to separate constants from inputs.
- Name parameters by domain meaning, using connector-local NOTES.md when available.
- Create a strict YAML scenario or Python pipeline under the connector's pending pipeline area.
- Include verification that checks structure, required fields, and success conditions.
- Run the narrowest test or icc_exec smoke check that proves the artifact loads.
What it can do on your machine
Read from SKILL.md and the folder at commit 035db30. 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
Crystallize From Wal loads about 313 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 149 words of instructions outside code blocks.
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 jianzhichun/emerge at commit 035db30, republished under its MIT licence (© jianzhichun). 149 words, ~313 tokens.
Download SKILL.mdSave it as
.claude/skills/crystallize-from-wal/SKILL.md (or your agent's skills folder).- name
- crystallize-from-wal
- description
- Use when an Emerge intent is marked synthesis_ready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
Crystallize From WAL
Use this when an intent has synthesis_ready evidence. The runtime provides WAL facts; Claude performs parameter selection and artifact authoring.
Workflow
- Gather all successful WAL samples for the intent.
- Compare samples to separate constants from inputs.
- Name parameters by domain meaning, using connector-local
NOTES.mdwhen available. - Create a strict YAML scenario or Python pipeline under the connector's pending pipeline area.
- Include verification that checks structure, required fields, and success conditions.
- Run the narrowest test or
icc_execsmoke check that proves the artifact loads.
Rules
- Do not preserve debug prints, temporary tracing, or one-off local paths.
- Do not promote the artifact directly unless a mechanism tool explicitly performs that transition.
- If WAL samples conflict, mark synthesis blocked with the reason and the missing evidence.
Output
Return the pending artifact path, the parameters inferred from WAL, verification evidence, and blockers if any.
© jianzhichun, 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/crystallize-from-wal of jianzhichun/emerge.
Open the folder on GitHubat commit 035db30
Compare with similar skills
Crystallize From Wal 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Crystallize From Wal this skilljianzhichun/emerge | 104 | — | ~313 | Automated safety check: Pass | MIT | |
| Intent Requirements IntakeYeachan-Heo/oh-my-claudecode | 40k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Browser Intentruvnet/ruflo | 74k | — | ~1.2k | Automated safety check: Notes | MIT | |
| Intent Recognitionn8n-io/n8n | 207k | — | ~7.1k | Automated safety check: Pass | Custom licence | |
| Exploring MCP Intent ClustersPostHog/posthog | 40k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Synthesisyologdev/yoyo-evolve | 1.9k | — | ~3.1k | Automated safety check: Pass | MIT |
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ruvnet/ruflo
Execute a natural-language browser intent via page-agent (browseract) when the target is easier to describe than to select — degrades gracefully when page-agent or an OpenAI-compatible LLM provider…
- Official
Intent Recognition
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Classifies automation requests using two decisions: anchor (which primitive owns the top-level control flow — workflow-anchored, agent-anchored, needs-clarification, or out-of-scope) and embedsother…
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Exploring MCP Intent Clusters
PostHog/posthog
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Multi-source research synthesis — aggregate and compare 3+ sources or any source 5KB using sub-agent dispatch and SharedState
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Questions about Crystallize From Wal
What does Crystallize From Wal do?
A skill your agent uses when an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact. Crystallize From Wal is an agent skill from jianzhichun/emerge. Use when an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
When should I use Crystallize From Wal?
Crystallize From Wal fits situations like: an Emerge intent is marked synthesisready and Claude must inspect successful WAL samples to create a conservative pending pipeline artifact.
How do I install Crystallize From Wal in Claude Code?
Run `npx skills add jianzhichun/emerge --skill crystallize-from-wal -a claude-code`. Or copy the skill folder (skills/crystallize-from-wal in jianzhichun/emerge) into .claude/skills/crystallize-from-wal in your project. Claude Code loads it when a task matches its description.
How do I install Crystallize From Wal in Codex?
Run `npx skills add jianzhichun/emerge --skill crystallize-from-wal -a codex`. Or copy the skill folder (skills/crystallize-from-wal in jianzhichun/emerge) into .agents/skills/crystallize-from-wal in your project. Codex loads it when a task matches its description.
Can I use Crystallize From Wal 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 jianzhichun/emerge --skill crystallize-from-wal -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/crystallize-from-wal, .gemini/skills/crystallize-from-wal, .github/skills/crystallize-from-wal and .opencode/skills/crystallize-from-wal in your project.
What does Crystallize From Wal need to run?
SKILL.md names no scripts, command-line tools or credentials: Crystallize From Wal is instructions for the agent only. Our summary lists: Python 3.
Does Crystallize From Wal 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 Crystallize From Wal 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 Crystallize From Wal use?
Crystallize From Wal 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 Crystallize From Wal use?
About 313 tokens (SKILL.md is roughly 1.3k 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 Crystallize From Wal?
Skills that share tags, products or a category with Crystallize From Wal: Intent Requirements Intake (Yeachan-Heo/oh-my-claudecode, 40k stars), Browser Intent (ruvnet/ruflo, 74k stars), Intent Recognition (n8n-io/n8n, 207k stars) and Exploring MCP Intent Clusters (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Crystallize From Wal?
jianzhichun (a GitHub user) maintains it in jianzhichun/emerge, which has 104 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on April 26, 2026.
Source: jianzhichun/emerge on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.