Huabu / http-native
AGENTS.md168 starsChanged 8 months agoMITView on GitHub
Load this guide when work should be handled by a visible Agent conversation instead of direct Space operations. An Agent may use Huabu's default Profile or another available Profile. The entry marked default: true is the first selectable external Profile used when Agent creation omits profileId. If no entry is marked, explicitly choose an available Profile; do not assume Built-In Pi is an implicit fallback. The huabu Profile uses Huabu's configured model provider. Other Profiles use their own configured runtimes…
We split this agents.md into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
Use JSON to choose a Profile, position, working directory, stable initial instructions, or optional parent conversation:
- Very specific: line 44
Use JSON without prompt and set X-Huabu-Agent-Start: false:
- Very specific: line 59
If you know the Agent Node but did not retain its creation response, resolve its existing thread association through INSPECT_NODES:
≈ “Common” is an estimate: at least 1 in 5 of the 36,368 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Creating and Prompting Agents
Load this guide when work should be handled by a visible Agent conversation instead of direct Space operations. An Agent may use Huabu's default Profile or another available Profile.
1. Discover available Profiles
curl -fsS -H "$AUTH" "$HUABU_RFS_URL/agent/profiles"The entry marked default: true is the first selectable external Profile used when Agent creation omits profileId. If no entry is marked, explicitly choose an available Profile; do not assume Built-In Pi is an implicit fallback.
The huabu Profile uses Huabu's configured model provider. Other Profiles use their own configured runtimes and do not depend on that provider.
2. Create and start an Agent
To use the configured default Profile, send the first prompt directly. This creates a visible Agent Node and immediately starts its first turn. An unconfigured or deleted default produces an explicit error rather than selecting another Agent.
curl -N -H "$AUTH" -H "Content-Type: text/plain" \
--data-binary @./prompt.txt "$HUABU_RFS_URL/agent"The response is SSE. Its created event contains the new nodeId, threadId, effective profileId, and parent-connection result. Save the threadId.
Use JSON to choose a Profile, position, working directory, stable initial instructions, or optional parent conversation:
curl -N -H "$AUTH" -H "Content-Type: application/json" \
-H "X-Huabu-Host-Thread-Id: $HUABU_THREAD_ID" \
--data-binary '{
"profileId": "profile-id",
"prompt": "Complete this bounded piece of work.",
"position": { "x": 1200, "y": 480 },
"workingDirPath": "/optional/absolute/path",
"additionalInitialPreamble": "Optional stable role instructions."
}' "$HUABU_RFS_URL/agent"The parent thread is only a best-effort lineage hint. Missing parents or rejected edges produce a warning in the successful creation response; they never prevent Agent Node creation.
3. Create without starting
Use JSON without prompt and set X-Huabu-Agent-Start: false:
curl -fsS -H "$AUTH" -H "Content-Type: application/json" \
-H "X-Huabu-Agent-Start: false" \
--data-binary '{
"profileId": "profile-id",
"position": { "x": 1200, "y": 480 }
}' "$HUABU_RFS_URL/agent"The JSON response contains the same creation metadata. The Agent remains idle until prompted.
4. Continue an Agent conversation
If you know the Agent Node but did not retain its creation response, resolve its existing thread association through INSPECT_NODES:
THREAD_ID="$(curl -fsS -H "$AUTH" -H "Content-Type: application/json" \
--data-binary '{"type":"INSPECT_NODES","ids":["node-123"]}' \
"$HUABU_RFS_URL/query" \
| node -e 'let s="";process.stdin.on("data",d=>s+=d).on("end",()=>process.stdout.write(JSON.parse(s).result.nodes[0]?.threadId ?? ""))')"
curl -N -H "$AUTH" -H "Content-Type: text/plain" \
--data-binary @./follow-up.txt \
"$HUABU_RFS_URL/agent/$THREAD_ID/prompt"Only Question Nodes with a non-empty existing association include threadId; non-Question Nodes and unbound Questions omit it. Inspection is read-only and never creates or realizes Agent state. The prompt endpoint never creates another Agent or changes its Profile. The response is SSE, and closing the connection stops delivery without aborting the durable turn.
An Agent can repeat the same create-and-prompt workflow to delegate recursively. Prefer direct work when another Agent adds no useful specialization, isolation, or parallelism.
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 28,693 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository22 other files it gives its agents.
- .agents/skills/vercel-composition-patterns/AGENTS.mdAGENTS.md
- .agents/skills/vercel-react-best-practices/AGENTS.mdAGENTS.md
- apps/server/src/prompt/external-agent/rfs-cli/agents.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- code-review-expertSkill
- releaseSkill
- review-agent-primitivesSkill
- review-huabu-agentSkill
- vercel-composition-patternsSkill
- vercel-react-best-practicesSkill
- web-design-guidelinesSkill
- deepv-slides-makerSkill
- hackmd-publisherSkill
- html-slides-makerSkill
- issue-trackerSkill
- paper-reviewerSkill
- paper-scoutSkill
- Create a user skillSkill
- spaceSkill
- Update a user skillSkill
- image-genSkill
- web-searchSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

