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Agent skill

Hep Graph

by agentlas-ai in agentlas-ai/Agentlas-OS

Build an Agentlas automation by describing it, list saved ones, or request a run.

Apache-2.0Auto-check: warningsAgent Workflows

Install Hep Graph

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add agentlas-ai/Agentlas-OS --skill hep-graph -a claude-code

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

GitHub CLI
$ gh skill install agentlas-ai/Agentlas-OS hep-graph --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/agentlas-ai/Agentlas-OS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/kimi/skills/hep-graph .claude/skills/hep-graph && 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
hep-graph
GitHub stars
1.6k
Token cost
~1.3k tokens
SKILL.md length
781 words
Files
1
Skills in repo
53
Repo updated
First seen
Licence
Apache-2.0

At a glance

Build an Agentlas automation by describing it, list saved ones, or request a run.

  • Works in 3 steps: Run "$CLI" graph show "" first and… → If the graph starts from a value (graph… → Request the run immediately once all…
  • Agent Workflows work in your project
  • SKILL.md covers Locate the CLI, New — build one by talking it…, List and Show, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Hep Graph is an agent skill from agentlas-ai/Agentlas-OS. Build an Agentlas automation by describing it, list saved ones, or request a run.

Its SKILL.md is about 1.3k 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 Agent Workflows. The repository describes itself as: Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model. The licence is Apache-2.0.

When your agent uses it

  • Agent Workflows work in your project

Example prompts

  • “/hep-graph”

Requirements

  • Node.js

Workflow steps

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

  1. Run "$CLI" graph show "" first and report what the graph does,
  2. If the graph starts from a value (graph show says so), require that value
  3. Request the run immediately once all required input is present

What it can do on your machine

Read from SKILL.md and the folder at commit cfdebf8. 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 (its code samples are bash).

    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

Hep Graph loads about 1.3k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 781 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningContains instruction-override wording (e.g. “without asking the user”)SKILL.md:16
    Say that plainly when you report back; do not tell the user their

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 agentlas-ai/Agentlas-OS at commit cfdebf8, republished under its Apache-2.0 licence (© agentlas-ai). 781 words, ~1,294 tokens.

Download SKILL.mdSave it as .claude/skills/hep-graph/SKILL.md (or your agent's skills folder).
name
hep-graph
description
Build an Agentlas automation by describing it, list saved ones, or request a run.

Update fallback: 자동 업데이트가 안 되면 hephaestus update를 한 번 실행하세요. 업데이트하지 않아도 현재 버전 명령은 그대로 동작합니다.

/hep-graph

Saved automation graphs live in the local Agentlas database, shared with the desktop app. This command reads that database and can ask for a graph to run.

Raw arguments: $ARGUMENTS

What this command can and cannot do. It lists graphs, shows what a graph does, and requests a run. It does not execute the graph — the desktop app is what runs it. Say that plainly when you report back; do not tell the user their automation ran.

Locate the CLI

bash
CLI=""
for candidate in \
  "$(command -v agentlas 2>/dev/null)" \
  "$HOME/.agentlas/runtime/current/bin/agentlas" \
  "./bin/agentlas"
do
  if [ -n "$candidate" ] && [ -x "$candidate" ]; then CLI="$candidate"; break; fi
done
[ -n "$CLI" ] || { echo "Agentlas CLI not found. Install it with: npm i -g agentlas" >&2; exit 1; }

New — build one by talking it through

With new <what they want> (or when the user describes an automation they want and no saved graph matches), run the CLI's interview. It asks the user things it must not decide for them — when it runs, whether a step goes outside, how many times a repeat may run.

The CLI reads answers from stdin, one per line. So: run it once with no answers to see the first questions, relay them to the user in their own words, get their answers, then run it again with every answer so far:

bash
printf '%s\n' "<answer 1>" "<answer 2>" "y" | "$CLI" graph new "<what they want>"

Rules that matter here:

  • Never invent an answer. If the user has not said when it runs, ask them — do not pick a time. The whole point of the interview is that these come from the person.
  • The interview proposes a grading checklist for steps that repeat until good enough (what must exist / what must not appear). Relay those items so the user can confirm or edit them — they are the pass/fail criteria, and the person should see them before saving.
  • If the user does not know or says you decide, pass that through verbatim (알아서 해주세요 / you decide). The CLI then takes the most conservative option and says what it chose. Do not decide on their behalf yourself.
  • The last line must be y to save. Until then nothing is written.
  • It is created switched off. Say so, and relay the two commands the CLI prints (graph show to look it over, automation on to turn it on).
  • If the CLI stops with "답을 받지 못해 여기서 멈췄습니다: <질문>" / "Stopped here without an answer to: <question>", it needed one more answer. Relay that exact question to the user and run again with the fuller list. Do not retry with a guess.

List

With no arguments, or with list:

bash
"$CLI" graph list

Report each graph with its trigger kind (schedule or input), step count, and whether it is on. If nothing is saved, say so and point at the desktop app's Graph page — do not invent graphs.

Show full SKILL.md (340 more words)Show less

Show

With show <name>:

bash
"$CLI" graph show "<name>"

The output is a tree, not a list — indentation is the wiring. Relay it as wiring, because on a surface with no canvas this is the only way the user can see where a graph branches. These marks must survive into your summary: a step that changes something outside, a step that asks first, a branch's [yes]/[no] sides, a ↩ back to … line (a repeat), a checklist under a verification step (the · [must] / [must not] lines — those items are exactly what the result is graded on), and a code step (a script the AI wrote runs there, not a model prompt). If the graph starts from a value the user provides, the output says so — carry that into the summary too.

Run

With run <name>, the user's direct command is the authority to request that run. Do not ask for a second yes: graph approval is captured when the graph is created, and adding another confirmation here makes an approved automation needlessly stall.

  1. Run "$CLI" graph show "<name>" first and report what the graph does, including any step that changes something outside.
  2. If the graph starts from a value (graph show says so), require that value from the user in their own words. This is missing execution input, not an approval prompt. Do not invent one or reuse an example from the graph.
  3. Request the run immediately once all required input is present:
bash
"$CLI" graph run "<name>" -y

If the graph starts from a value, pass it — without it the CLI refuses, because a graph run with a blank value silently produces something else:

bash
"$CLI" graph run "<name>" -y --input "<the value the user gave>"

Report exactly what the CLI reported: the run was requested, the desktop app picks it up within a minute while open, and a closed app runs it on next open. If the CLI refuses because the automation is switched off, relay that refusal and its reason rather than retrying.

Failure

If the CLI exits non-zero, show its message verbatim and stop. Do not substitute a guess about why, and do not retry a run request.

© agentlas-ai, Apache-2.0. 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 kimi/skills/hep-graph of agentlas-ai/Agentlas-OS.

Open the folder on GitHubat commit cfdebf8

Compare with similar skills

Hep Graph 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.

Hep Graph compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hep Graph this skillagentlas-ai/Agentlas-OS1.6k—~1.3kAutomated safety check: WarnApache-2.0
MCP Server Builderanthropics/skills180k64 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

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Categories

Questions about Hep Graph

What does Hep Graph do?

Build an Agentlas automation by describing it, list saved ones, or request a run. Hep Graph is an agent skill from agentlas-ai/Agentlas-OS. Build an Agentlas automation by describing it, list saved ones, or request a run.

When should I use Hep Graph?

Hep Graph fits situations like: agent Workflows work in your project.

How do I install Hep Graph in Claude Code?

Run `npx skills add agentlas-ai/Agentlas-OS --skill hep-graph -a claude-code`. Or copy the skill folder (kimi/skills/hep-graph in agentlas-ai/Agentlas-OS) into .claude/skills/hep-graph in your project. Claude Code loads it when a task matches its description.

How do I install Hep Graph in Codex?

Run `npx skills add agentlas-ai/Agentlas-OS --skill hep-graph -a codex`. Or copy the skill folder (kimi/skills/hep-graph in agentlas-ai/Agentlas-OS) into .agents/skills/hep-graph in your project. Codex loads it when a task matches its description.

Can I use Hep Graph 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 agentlas-ai/Agentlas-OS --skill hep-graph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hep-graph, .gemini/skills/hep-graph, .github/skills/hep-graph and .opencode/skills/hep-graph in your project.

What does Hep Graph need to run?

SKILL.md names no scripts, command-line tools or credentials: Hep Graph is instructions for the agent only. Our summary lists: Node.js.

Does Hep Graph 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 Hep Graph safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): contains instruction-override wording (e.g. “without asking the user”). Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Hep Graph use?

Hep Graph is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hep Graph use?

About 1.3k tokens (SKILL.md is roughly 5.2k 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 Hep Graph?

Skills that share tags, products or a category with Hep Graph: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hep Graph?

agentlas-ai (a GitHub organization) maintains it in agentlas-ai/Agentlas-OS, which has 1,575 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on October 6, 2026.

Source: agentlas-ai/Agentlas-OS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.