Agent Builder
n8n-io/n8n
Load immediately after an Agent intent. An agent skill from n8n-io/n8n.
Integrate DashClaw SDK into any agent using the 4-step governance loop
$ npx skills add ucsandman/DashClaw --skill instrument-agent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ucsandman/DashClaw instrument-agent --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/ucsandman/DashClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .claude/skills/instrument-agent && 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 "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .claude/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agentType 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 ucsandman/DashClaw --skill instrument-agent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ucsandman/DashClaw instrument-agent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ucsandman/DashClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .agents/skills/instrument-agent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .agents/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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 ucsandman/DashClaw --skill instrument-agent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ucsandman/DashClaw instrument-agent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ucsandman/DashClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .cursor/skills/instrument-agent && 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 "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .cursor/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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/ucsandman/DashClaw.git --path .claude/skills/dashclaw-agent/instrument-agent--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 ucsandman/DashClaw --skill instrument-agent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ucsandman/DashClaw instrument-agent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ucsandman/DashClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .gemini/skills/instrument-agent && 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 "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .gemini/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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 ucsandman/DashClaw instrument-agentInstalls 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 ucsandman/DashClaw --skill instrument-agent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ucsandman/DashClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .github/skills/instrument-agent && 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 "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .github/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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 ucsandman/DashClaw --skill instrument-agent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ucsandman/DashClaw instrument-agent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ucsandman/DashClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/dashclaw-agent/instrument-agent .opencode/skills/instrument-agent && 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 "instrument-agent" agent skill from https://github.com/ucsandman/DashClaw/tree/main/.claude/skills/dashclaw-agent/instrument-agent into .opencode/skills/instrument-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "instrument-agent", 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.
instrument-agentIntegrate DashClaw SDK into any agent using the 4-step governance loop
Instrument Agent is an agent skill from ucsandman/DashClaw. Integrate DashClaw SDK into any agent using the 4-step governance loop
Its SKILL.md is about 2.2k 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 AI & LLM Engineering, covering Building AI agents. It works with Model Context Protocol. The repository describes itself as: Remote approvals, policy checks, and execution evidence for unattended AI agents. The licence is MIT.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 704824d. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
nodenpmpipcurljqFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npm, pip and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
DASHCLAW_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Instrument Agent loads about 2.2k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 352 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.
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.
The full file from ucsandman/DashClaw at commit 704824d, republished under its MIT licence (© ucsandman). 352 words, ~2,210 tokens.
.claude/skills/instrument-agent/SKILL.md (or your agent's skills folder).Help developers add DashClaw governance to any AI agent. Walk through the 4-step governance loop with working code.
Every governed decision follows this deterministic flow:
1. Guard → "Can I do this?" (POST /api/guard)
2. Record → "I am doing this." (POST /api/actions)
3. Verify → "I believe this is true." (POST /api/assumptions)
4. Outcome → "This was the result." (PATCH /api/actions/:id)npm install dashclawimport { DashClaw } from 'dashclaw';
const claw = new DashClaw({
baseUrl: process.env.DASHCLAW_BASE_URL,
apiKey: process.env.DASHCLAW_API_KEY,
agentId: 'my-agent'
});pip install dashclawfrom dashclaw import DashClaw
claw = DashClaw(
base_url=os.environ["DASHCLAW_BASE_URL"],
api_key=os.environ["DASHCLAW_API_KEY"],
agent_id="my-agent"
)Create a session to track the full lifecycle of your agent's work. Sessions enable monitoring, recovery, and continuity across restarts.
// Create a session at agent startup
const session = await fetch(`${baseUrl}/api/sessions`, {
method: 'POST',
headers: { 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json' },
body: JSON.stringify({ agent_id: 'my-agent', metadata: { task: 'deploy-pipeline' } })
}).then(r => r.json());
// Report status during execution
await fetch(`${baseUrl}/api/sessions/${session.id}`, {
method: 'PATCH',
headers: { 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json' },
body: JSON.stringify({ status: 'running', checkpoint: { step: 'guard-check' } })
});Session lifecycle is optional — all governance loop steps work without it — but it provides visibility into long-running agent tasks and enables automatic recovery when sessions are interrupted.
const decision = await claw.guard({
action_type: 'deploy',
declared_goal: 'Deploy build #402 to production',
risk_score: 85,
systems_touched: ['production', 'database'],
reversible: false
});
// decision.decision: 'allow' | 'warn' | 'block' | 'require_approval'
if (decision.decision === 'block') {
console.log('Blocked:', decision.reason);
return;
}decision = claw.guard(
action_type="deploy",
declared_goal="Deploy build #402 to production",
risk_score=85,
systems_touched=["production", "database"],
reversible=False
)
if decision["decision"] == "block":
print(f"Blocked: {decision['reason']}")
returnGuard response shape:
{
"decision": "require_approval",
"action_id": "act_gd_abc123",
"reason": "Risk score exceeds org threshold",
"signals": ["Production access", "High risk score"],
"risk_score": 75,
"agent_risk_score": 85,
"recovery_recipes": [
{ "action": "reduce_scope", "description": "Deploy to staging first" }
]
}The guard may enforce these policy types — your agent should be prepared to respond to each:
permission_escalation — The action requires a higher permission_level than currently granted. Re-request with elevated permissions or abort.green_contract — The action requires test verification before execution (e.g., tests must pass before deploying). Run tests and include evidence in the guard request.branch_freshness — The action targets a stale branch. Pull latest changes or rebase before retrying.When the guard blocks an action, check the recovery_recipes array in the response for actionable remediation steps.
const action = await claw.createAction({
action_type: 'deploy',
declared_goal: 'Deploy build #402 to production',
risk_score: 85,
reversible: false,
systems_touched: ['production']
});
// action.action_id: 'ar_abc123'action = claw.create_action(
action_type="deploy",
declared_goal="Deploy build #402 to production",
risk_score=85,
reversible=False,
systems_touched=["production"]
)await claw.recordAssumption({
action_id: action.action_id,
assumption: 'Staging tests passed successfully',
source: 'ci-pipeline'
});claw.record_assumption(
action_id=action["action_id"],
assumption="Staging tests passed successfully",
source="ci-pipeline"
)await claw.updateOutcome(action.action_id, {
status: 'completed', // or 'failed'
output_summary: 'Build #402 deployed successfully to production',
timestamp_end: new Date().toISOString(),
// Optional — populates Analytics cost/token charts. When tokens + model
// are supplied without an explicit cost_estimate, the server derives
// cost from the configured pricing table.
tokens_in: result.usage?.input_tokens,
tokens_out: result.usage?.output_tokens,
model: result.model,
});claw.update_outcome(action["action_id"],
status="completed",
output_summary="Build #402 deployed successfully to production",
# Optional — populates Analytics cost/token charts.
tokens_in=response.usage.input_tokens,
tokens_out=response.usage.output_tokens,
model=response.model,
)import { DashClaw } from 'dashclaw';
const claw = new DashClaw({
baseUrl: process.env.DASHCLAW_BASE_URL,
apiKey: process.env.DASHCLAW_API_KEY,
agentId: 'deploy-agent'
});
async function governedDeploy(buildId) {
// 1. Guard
const decision = await claw.guard({
action_type: 'deploy',
declared_goal: `Deploy build #${buildId} to production`,
risk_score: 85,
systems_touched: ['production'],
reversible: false
});
if (decision.decision === 'block') {
console.log('Blocked:', decision.reason);
return;
}
// 2. Record
const action = await claw.createAction({
action_type: 'deploy',
declared_goal: `Deploy build #${buildId} to production`,
risk_score: 85,
reversible: false
});
// 3. Verify assumptions
await claw.recordAssumption({
action_id: action.action_id,
assumption: 'All CI checks passed'
});
// 4. Execute and record outcome
try {
await actualDeploy(buildId);
await claw.updateOutcome(action.action_id, {
status: 'completed',
output_summary: `Build #${buildId} deployed successfully`
});
} catch (err) {
await claw.updateOutcome(action.action_id, {
status: 'failed',
output_summary: err.message
});
}
}| Action Type | Risk Score | Reversible | Example |
|---|---|---|---|
| deploy | 75-90 | false | Production deployment |
| api_call | 20-40 | true | External API request |
| file_write | 15-30 | true | Local file modification |
| database | 50-80 | false | Schema migration, data deletion |
| security | 80-95 | false | Key rotation, permission changes |
| build | 10-25 | true | npm install, compilation |
| notify | 5-15 | true | Send email, Slack message |
Risk scoring rule: DashClaw uses the HIGHER of computed risk and agent-reported risk. Always report honestly — inflating risk is better than under-reporting.
When guard returns require_approval:
if (decision.decision === 'require_approval') {
console.log('Waiting for human approval...');
await claw.waitForApproval(decision.action_id, {
timeout: 300000 // 5 minutes
});
// Continues after approval, throws ApprovalDeniedError if denied
}| Variable | Required | Description |
|---|---|---|
DASHCLAW_BASE_URL | Yes | DashClaw instance URL |
DASHCLAW_API_KEY | Yes | API authentication key |
DASHCLAW_AGENT_ID | No | Default agent identifier |
After instrumenting, drive a real end-to-end check against your DashClaw instance with the live SDK smoke test:
# Node SDK round-trip (guard → createAction → updateOutcome)
node scripts/_run-with-env.mjs scripts/test-sdk-live.mjs
# Python equivalent
node scripts/_run-with-env.mjs scripts/run-sdk-live-python.mjs
# Or just confirm the instance is reachable
curl -sf "$DASHCLAW_BASE_URL/api/health" | jq '.status'Then refresh /decisions on your DashClaw instance — your most recent governed action should appear within seconds.
© ucsandman, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/dashclaw-agent/instrument-agent of ucsandman/DashClaw.
Open the folder on GitHubat commit 704824d
Instrument Agent 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 |
|---|---|---|---|---|---|---|
| Instrument Agent this skillucsandman/DashClaw | 310 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Agent Buildern8n-io/n8n | 207k | — | ~2.5k | Automated safety check: Pass | Custom licence | |
| Summarizeswarmclawai/swarmclaw | 688 | — | ~531 | Automated safety check: Pass | MIT | |
| Agent Squad Python Guide2FastLabs/agent-squad | 7.8k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| Agent Squad for TypeScript2FastLabs/agent-squad | 7.8k | — | ~4.3k | Automated safety check: Pass | Apache-2.0 | |
| Agent Frameworkjihadkhawaja/Egroo | 178 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 |
n8n-io/n8n
Load immediately after an Agent intent. An agent skill from n8n-io/n8n.
swarmclawai/swarmclaw
Summarize or extract text/transcripts from URLs, podcasts, YouTube videos, and local files using the summarize CLI.
2FastLabs/agent-squad
Map of the agent-squad Python framework for async multi-agent orchestration: which agent, classifier, storage and tool provider to pick, and the pitfalls to avoid.
2FastLabs/agent-squad
Guide to building Node.js and TypeScript apps on the agent-squad package: orchestrator, agent types, classifier routing, storage, retrievers and MCP tools.
jihadkhawaja/Egroo
Build, extend, and debug AI agents in Egroo using the Microsoft Agent Framework (C .NET).
openma-ai/open-managed-agents
Use the openma platform to build, deploy, and manage AI agents.
ucsandman/DashClaw
Governance behavior for AI agents governed by DashClaw. An agent skill from ucsandman/DashClaw.
ucsandman/DashClaw
The single command that gets a DashClaw change ON MAIN AND LIVE — it resolves everything blocking production, never defers, and never hands back a checklist.
ucsandman/DashClaw
Turn a bug symptom into a structured, reproducible bug report — summary, environment, exact repro steps, actual vs expected, and evidence (logs, error text, failing route/test) — and then optionally…
ucsandman/DashClaw
Governance behavior for Muse agents governed by DashClaw. An agent skill from ucsandman/DashClaw.
ucsandman/DashClaw
Contribute to the DashClaw codebase — architecture, scaffolding, tests, CI
ucsandman/DashClaw
Set up compliance exports, drift detection, evaluations, scoring, and learning analytics
Works with
Categories
Integrate DashClaw SDK into any agent using the 4-step governance loop. Instrument Agent is an agent skill from ucsandman/DashClaw.
Instrument Agent fits situations like: tasks that involve Building AI agents.
Run `npx skills add ucsandman/DashClaw --skill instrument-agent -a claude-code`. Or copy the skill folder (.claude/skills/dashclaw-agent/instrument-agent in ucsandman/DashClaw) into .claude/skills/instrument-agent in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ucsandman/DashClaw --skill instrument-agent -a codex`. Or copy the skill folder (.claude/skills/dashclaw-agent/instrument-agent in ucsandman/DashClaw) into .agents/skills/instrument-agent in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ucsandman/DashClaw --skill instrument-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/instrument-agent, .gemini/skills/instrument-agent, .github/skills/instrument-agent and .opencode/skills/instrument-agent in your project.
Going by SKILL.md and its folder, Instrument Agent needs the command-line tools its instructions call (node, npm, pip, curl and jq) and credentials named DASHCLAW_API_KEY. Our summary lists: Python 3; Node.js; A credential in DASHCLAW_API_KEY.
SKILL.md contains no URLs. Its commands use npm, pip and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Instrument Agent is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Instrument Agent: Agent Builder (n8n-io/n8n, 207k stars), Summarize (swarmclawai/swarmclaw, 688 stars), Agent Squad Python Guide (2FastLabs/agent-squad, 7.8k stars) and Agent Squad for TypeScript (2FastLabs/agent-squad, 7.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ucsandman (a GitHub user) maintains it in ucsandman/DashClaw, which has 310 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 6, 2026.
Source: ucsandman/DashClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.