Agent skill

Herdr Agent

by luongnv89 in luongnv89/skills

Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; help lists every operation.

MITAuto-check passedAgent Workflows

Install Herdr Agent

skills CLI
$ npx skills add luongnv89/skills --skill herdr-agent -a claude-code

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

GitHub CLI
$ gh skill install luongnv89/skills herdr-agent --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/luongnv89/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/herdr-agent .claude/skills/herdr-agent && 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
herdr-agent
GitHub stars
131
Token cost
~4.8k tokens
SKILL.md length
2,523 words
Files
29 (incl. scripts, references)
Skills in repo
37
Repo updated
First seen
Licence
MIT

At a glance

Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; help lists every operation.

  • Works in 8 steps: Resolve Root Context → Spawn and Ready the Fleet → Resolve One Exact Target → …
  • Non-Herdr terminals
  • SKILL.md covers Choose the Workflow, Answer a Help Request, Check Prerequisites and Follow Non-Negotiable Rules, plus 12 more sections
  • Runs Python and Shell scripts from its folder; calls python3

What it does

Herdr Agent is an agent skill from luongnv89/skills. Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; help lists every operation. Use for Herdr fleets. Don't use for tmux, screen, or non-Herdr terminals.

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 32 other files, including scripts and reference files (for example `docs/README.md`, `evals/evals.json` and `references/context-succession.md`). Compatibility notes: Requires herdr 0.9.0 or later on PATH and a running Herdr server (herdr status) for every operation except help, which runs no herdr command. Default…

It sits in Agent Workflows, covering Subagents. It works with tmux. The repository describes itself as: Supercharge your AI agents/bots with reusable skills. The licence is MIT.

When your agent uses it

  • Non-Herdr terminals
  • Tasks that involve Subagents

Example prompts

  • “/herdr-agent”

Requirements

  • Python 3
  • A Bash shell
  • Compatibility (from SKILL.md): Requires herdr 0.9.0 or later on PATH and a running Herdr server (`herdr status`) for every operation except `help`, which runs no herdr command. Default same-kind launches also require `pane process-info` to return full argv; `--without flags` explicitly opts out.

Workflow steps

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

  1. Resolve Root Context
  2. Spawn and Ready the Fleet
  3. Resolve One Exact Target
  4. Prompt Safely
  5. Read and Verify
  6. Monitor and Report
  7. Broadcast, Steer, or Tear Down
  8. Hand Off the Orchestrator Role

What it can do on your machine

Read from SKILL.md and the folder at commit 891c720. 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

    Ships 6 files in scripts/ (Python and Shell, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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.

  • Compatibility

    Requires herdr 0.9.0 or later on PATH and a running Herdr server (`herdr status`) for every operation except `help`, which runs no herdr command. Default same-kind launches also require `pane process-info` to return full argv; `--without flags` explicitly opts out.

    From compatibility in the SKILL.md frontmatter.

Context cost

Herdr Agent loads about 4.8k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 2,523 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~20k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from luongnv89/skills at commit 891c720, republished under its MIT licence (© luongnv89). 2,523 words, ~4,828 tokens.

Download SKILL.mdSave it as .claude/skills/herdr-agent/SKILL.md (or your agent's skills folder). This skill also uses 28 other files; get the full folder from GitHub.
name
herdr-agent
description
Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; `help` lists every operation. Use for Herdr fleets. Don't use for tmux, screen, or non-Herdr terminals.
compatibility
Requires herdr 0.9.0 or later on PATH and a running Herdr server (`herdr status`) for every operation except `help`, which runs no herdr command. Default same-kind launches also require `pane process-info` to return full argv; `--without flags` explicitly opts out.
license
MIT
effort
medium
metadata.version
3.2.0
metadata.author
Luong NGUYEN <luongnv89@gmail.com>

Herdr Agent

Build and control an AI-agent fleet in the root agent's Herdr tab. Keep the root pane as orchestrator; add each sub-agent as a right-hand split running the main agent's own launch profile; equalize all columns; then start, prompt, wait, read, monitor, steer, or tear down through the herdr CLI.

Use Herdr concepts, not tmux assumptions. Let the server do the work: herdr agent prompt --wait submits and waits in one request, herdr agent wait is event-driven, and herdr api snapshot reports the whole fleet in one call. Relay reply deltas rather than whole panes to protect the context and token budget.

Choose the Workflow

RequestFollow
help, or what this does and how to drive itHelp in references/help-request.md — answer and stop
Spawn sub-agents beside rootPhases 1–2, then 4–5 if assigning work
Message an existing agentPhases 3–5
Read without sendingPhase 3, then Phase 5 read only
Check what the fleet is doingPhase 6
Broadcast to a fleetPhases 3 and 7
Focus/steer a panePhase 3, then Phase 7
Close workersPhase 7 teardown
Main agent's own context is filling upPhase 8 HANDOFF

Read only the reference needed by that branch:

  • See references/herdr-recipes.md for guarded grid spawning, equalization semantics, multi-line prompts, focus, and troubleshooting.
  • See references/launch-profile.md for where a worker's kind, model, thinking level, and flags come from, the kind gate, and what never carries over.
  • See references/delivery-and-waiting.md for the one-call prompt contract, error codes, wait semantics, reading replies, and the no-agent fallback.
  • See references/fleet-monitoring.md for snapshot status, sidebar badges, notifications, and the run report.
  • See references/context-succession.md for the main agent's context gate, HANDOFF procedure, and handoff brief template.
  • See references/final-report.md for the closing report's status words, required parts, and examples.

Answer a Help Request

Resolve this branch before Prerequisites. A help request runs no herdr command, touches no pane, and changes nothing, because someone asking how this works may not have Herdr installed yet. Take it on help, --help, /herdr-agent help, or any plain question about what the skill does or how to drive it. Answer, then stop: no fleet work, no completion report.

The full help text is in references/help-request.md. For a narrower question such as how to broadcast, answer from that one phase instead of printing the whole block, and name the phase so the user can ask for it again by name.

Done when: the user has the summary or their specific answer, and no herdr command ran.

Check Prerequisites

  1. Run command -v herdr and herdr status. If the server is unavailable, ask the user to start Herdr from a real terminal; never run bare herdr from a non-TTY shell.
  2. Confirm HERDR_ENV=1. Outside a Herdr pane, do not inspect or control the focused session. If check 1 or 2 fails, stop: the run ends BLOCKED.
  3. Resolve the root pane, tab, and workspace from HERDR_PANE_ID, HERDR_TAB_ID, and HERDR_WORKSPACE_ID, or from herdr pane current --current and list/get commands.
  4. Run agents directly in Herdr panes. Do not nest tmux when agent detection is required.
  5. Treat the installed CLI as authoritative. Check uncertain commands with herdr <group> rather than inventing flags. Client and server versions can differ after an update; herdr status says whether the server supports what you are about to use.

Follow Non-Negotiable Rules

  1. Keep root as a role. Never replace or close the root pane during fleet work. The one exception is a Phase 8 HANDOFF, where the orchestrator role migrates to a ready successor pane; even then the outgoing pane is retired to read-only, never closed without Rule 8 confirmation.
  2. Run exactly one orchestrator. Only the current main agent writes to fleet panes. After a HANDOFF ack, the outgoing agent issues no further prompts, splits, or closes.
  3. Parse IDs. Read opaque workspace/tab/pane IDs from JSON; never infer them from display order. A pane moved to another workspace gets a new ID.
  4. Use one equal-width row. Split the current rightmost pane right, keep every worker in the root tab, then run the equalizer. Create separate tabs only when the user explicitly requests isolation.
  5. Fail closed before writes. Herdr refuses a blocked target itself, but not a working one, and its wait tracks lifecycle state rather than one turn. Reject missing, ambiguous, working, or unverifiable targets yourself before dispatching.
  6. Wait before follow-ups. Never prompt while an agent is working. Every follow-up is its own agent prompt --wait cycle.
  7. Surface blockers. A trust, auth, or permission prompt needs a human. Focus the pane, notify, and never answer the dialog for them.
  8. Confirm destruction. Closing panes, tabs, workspaces, or the server can lose work. Obtain explicit approval and preserve the orchestrator pane unless the user says otherwise.
  9. Gate your own context. Self-check at every Phase 8 gate point; at or above the threshold, HANDOFF instead of continuing to fill this window.
  10. Mirror the main agent. Start every worker, including a HANDOFF successor, on the inherited launch profile: the same harness kind, model, thinking level, and setup flags as the main agent. Change only what the user names for that worker, or what a calling skill's launch contract requires (for example --without flags for a skill that demands bare launches). A field is named only by a concrete value: a kind, a model ID or alias, a thinking level, or a flag. Ask when a request is vague ("something cheaper") or names a model from another harness without a kind. A worker of a different kind inherits nothing else. Never guess a value you cannot read: model or thinking may be reported UNKNOWN, but unreadable same-kind setup flags abort the launch unless --without flags explicitly opts out.

Phase 1 — Resolve Root Context

bash
command -v herdr >/dev/null || { echo "Error: herdr is not installed" >&2; exit 1; }
test "${HERDR_ENV:-}" = 1 || { echo "Error: not running inside a Herdr pane" >&2; exit 1; }
herdr status || { echo "Error: Herdr server is unavailable" >&2; exit 1; }
root_pane="${HERDR_PANE_ID:?}"; root_tab="${HERDR_TAB_ID:?}"; ws="${HERDR_WORKSPACE_ID:?}"

Resolve project_dir from the root pane's cwd, falling back to the current directory. Set here to the skill's scripts/ directory with the resolver in references/herdr-recipes.md, which probes repo-local installs before global ones. Every later script call uses "$here/…".

Done when: server status passes and concrete root_pane, root_tab, ws, project_dir, and here values are recorded.

Phase 2 — Spawn and Ready the Fleet

Before spawning, define each worker's unique name, task, and expected deliverable. Placement and launch are two steps: herdr agent start never creates or moves layout, and requires a pane already sitting at its shell prompt.

Resolve the inherited launch profile once per spawn wave, as its own tool call before the call that splits, so the user sees it before any agent starts:

bash
python3 "$here/launch_profile.py" --root-pane "$root_pane" \
  --main-model "$main_model" --main-thinking "$main_thinking" >/dev/null

Set main_model and main_thinking to your own model ID and thinking level, and leave either one empty rather than guess. On Claude Code, leave main_thinking empty, because the script reads CLAUDE_EFFORT. Relay the summary line to the user before the first split, including any ⚠ or warning: line. A worker with an UNKNOWN model or thinking level still starts on its config default. Missing or malformed root argv aborts a same-kind launch before the split; --without flags is the explicit reduced-inheritance opt-out. If the user already declined bypass for this run, pass --without bypass on every worker. references/launch-profile.md has the source order, per-kind flags, and what never carries over.

Use the canonical spawn_sub workflow in references/herdr-recipes.md:

  1. Run next_grid_split.py --root-pane "$root_pane" to plan the rightmost split.
  2. Split with --direction right --no-focus in project_dir, passing --env "HERDR_ROLE=<name>" so the worker can read its own role instead of being told it in every prompt.
  3. Parse the new pane ID from JSON.
  4. Run next_grid_split.py --equalize --root-pane "$root_pane"; abort on any error or non-convergence.
  5. Rename the pane, then start it by running the same command plus --start <name> --pane <id> --timeout 60000. Add only what the user named: --kind, --model, --thinking, --without bypass|flags, or native flags after --. The command runs herdr agent start on the profile.
  6. Badge the worker with its job: python3 "$here/badge.py" <name> --title "<job>" --token role=<role>.

agent start is the readiness gate: it returns only once Herdr detects the expected agent and considers it interactive-ready, and returns agent_not_ready immediately if the agent booted into a dialog. There is no separate readiness pass. Names must match [a-z][a-z0-9_-]{0,31} and be unique among live agents. Never fold the task into argv.

Confirm the fleet with python3 "$here/fleet_status.py" --tab "$root_tab" --fail-on-blocked before assigning any work.

Done when: every worker has a unique name and pane ID in root_tab, the layout widths differ by at most one cell, root remains active, the launch-profile summary reached the user, and every start returned success.

Phase 3 — Resolve One Exact Target

Run herdr agent get <name> or herdr pane get <pane-id>. If a name is missing or ambiguous, list agents and ask; never silently retarget. agent_not_found means the pane hosts no detected agent — start one, or take the pane-surface fallback in references/delivery-and-waiting.md. Record both the name and pane ID and use that same ID for every later mutation.

Done when: one existing target resolves uniquely, and its name, pane ID, and current status are recorded.

Show full SKILL.md (1,036 more words)Show less

Phase 4 — Prompt Safely

bash
python3 "$here/preflight_send.py" "$target" >/dev/null || exit $?
herdr agent prompt "$target" "$task" --wait --timeout 180000

The preflight refuses working (2), blocked (3), unverifiable (4), and no-agent (5) targets. The prompt then submits text plus Enter as one ordered write honoring bracketed paste, refuses a blocked target server-side before writing anything, gates on observed activity, and waits for the first settled state — all in one request. Submission and waiting are atomic, so no transcript baseline or completion marker is needed: there is no gap between send and wait to race.

Do not add --until idle --until done; those are the --wait defaults. Use --until only for a state-specific wait such as --until blocked.

Done when: the prompt returned success, or a named error code was propagated.

Phase 5 — Read and Verify

Map the failure first. agent_blocked means nothing was sent and a human is needed. agent_prompt_stalled means it was submitted but no activity followed — inspect, never blindly resend. timeout means no settled state inside the budget. Propagate all three; do not report them as replies.

On success, read a capped transcript and relay only the relevant delta:

bash
herdr agent read "$target" --source recent-unwrapped --lines 80

Accept idle or done as settled; they differ only in whether the completion has been marked seen. If raising --lines reveals no more output, the agent is on the terminal's alternate screen — use the file fallback in references/delivery-and-waiting.md rather than a bigger line count.

Done when: the reply delta came from herdr agent read after an idle or done status, or the blocked/stalled/timeout code is reported and nothing more was sent.

Phase 6 — Monitor and Report

bash
python3 "$here/fleet_status.py" --tab "$root_tab"

One herdr api snapshot call renders every agent's status, badge and title, sorted by attention, at flat cost for any fleet size. Prefer it over per-agent herdr agent get polling, which costs N round trips and can report a fleet state that never existed at one instant.

Keep the human oriented without making them read panes:

  • Badge each worker as its job changes: python3 "$here/badge.py" <name> --token phase=<phase>. Display-only, so it never perturbs waits or rollups.
  • Notify only for events that need them: herdr notification show "Agent blocked" --body "<name> needs input" --sound request, and once at run completion with --sound done.

See references/fleet-monitoring.md for field caps, token semantics, and workspace-level rollups.

Done when: the current fleet state came from a snapshot call, not from memory of what was dispatched.

Phase 7 — Broadcast, Steer, or Tear Down

  • Broadcast: run "$here/broadcast.sh" "<task>" <targets...>. It resolves all targets from one agent list, dedupes, refuses unsafe ones, dispatches agent prompt --wait concurrently, and maps every error code to a reason. HAC_BADGE=1 badges each row with its phase.
  • Steer: focus with herdr agent focus <name>, which also marks that agent's completion seen. For follow-ups, repeat Phases 4–5.
  • Tear down: after explicit confirmation, close only worker panes created by this run. If the user declines or does not answer, close nothing and record the teardown as skipped. Close the root tab, workspace, or server only when explicitly requested. Never run herdr server stop from an active session unless the user intends to stop every pane process.

Done when: every requested target has a recorded outcome and destructive actions match the user's confirmed scope.

Phase 8 — Hand Off the Orchestrator Role

Long fleet runs outlive one context window. Self-check your own usage at three gate points — before a spawn wave, before a broadcast, and after each relayed reply — never mid-cycle between a dispatch and its wait. HANDOFF when self-reported usage is at or above the threshold (default 50%); when usage is UNKNOWN, apply the counter fallback in the reference below.

HANDOFF spawns a successor with the same Phase 2 machinery — main-g<N> in the root tab, equalized, started on the inherited launch profile so it runs your harness, model, and thinking level — then delivers a compact handoff brief through the Phase 4 cycle and waits for the ack HANDOFF ACCEPTED gen=<N> fleet=<k>. After the ack, that pane is the orchestrator; this pane goes read-only and announces the new one with herdr agent focus main-g<N>. A successor that fails to start or never acks means the HANDOFF failed: stay main, report the orphan pane, and ask before closing it.

Read references/context-succession.md for the gate-point table, UNKNOWN fallback logging, full procedure, and the brief template. Never paste transcripts or diffs into a brief.

Done when: the gate decision is recorded with a percentage or an explicit UNKNOWN fallback, and any HANDOFF has a ready successor pane, a delivered brief, a received ack, and no write from the outgoing pane afterward.

Verify Expected Output

Expected final report for a successful fleet operation:

text
Result: COMPLETE — spawned reviewer and tests; both replied
Evidence:
  herdr status: ok · root kept w26:p1 · 3 equal-width columns
  Profile: claude · claude-opus-5[1m] · thinking max (inherited)
  fleet_status.py: reviewer=done, tests=idle · 2 replies captured, 0 blocked, 0 timed out
Uncertainty: reply content relayed as written, not checked against the task
Decision: No approval needed.

Acceptance criteria:

  • A help request prints the usage summary, runs no herdr command, and emits no completion report.
  • herdr status succeeds and every target resolves uniquely.
  • Root remains in its original pane and all default workers share its tab.
  • Spawned columns are equal within one terminal cell.
  • Every worker runs the main agent's launch profile (kind, model, thinking level, setup flags) except fields the user named. UNKNOWN model/thinking values and inherited permission bypass are reported; unreadable same-kind setup flags fail closed unless explicitly disabled.
  • Every prompt passed preflight and returned either success or a named error code.
  • Every agent ends as settled, blocked, stalled, timed out, failed, or skipped — none disappear from the report.
  • The closing status came from fleet_status.py, not from recollection.
  • Errors and destructive confirmations are surfaced explicitly.
  • The context gate is evaluated at each gate point, and any HANDOFF ends with exactly one acked orchestrator.
  • Every run except help ends with the final report, which passes its four reader checks: result on the first line, facts separated from assumptions, every claim traced to evidence, next decision named. Without user feedback, human understanding stays unconfirmed.

Handle Edge Cases

Read references/edge-cases.md when a target is blocked, agent_not_found, or unknown; a name collides; the grid passes four panes or will not equalize; the workspace or tab is wrong; a successor never acks; root process-info lacks full argv; or a start times out after inheriting a flag.

Emit the Step Completion Report

text
◆ Herdr Agent ([operation])
··································································
  Server:              √ pass
  Root resolved:       √ pass (pane · tab · workspace)
  Targets:             √ pass (N/N unique)
  Launch profile:      √ pass (kind · model · thinking · N flags; UNKNOWN and ⚠ named — if spawning; otherwise — n/a)
  Layout/readiness:    √ pass (if spawning; otherwise — n/a)
  Delivery:            √ pass (if prompting; otherwise — n/a)
  Replies:             √ pass (settled · blocked/stalled/timeouts reported)
  Fleet snapshot:      √ pass (N agents · statuses)
  Context gate:        √ pass (P% or UNKNOWN · continue | HANDOFF → main-gN)
  Destructive action:  — none (or confirmed scope)
  Result:              PASS | FAIL | PARTIAL

Write the Final Report

After the Step Completion Report, print the final report from references/final-report.md: Result: (COMPLETE, PARTIAL — <reason>, or BLOCKED — <reason>), Evidence: (only checks that ran), Uncertainty:, then Decision: (the approval needed, or No approval needed.). A help request skips it.

© luongnv89, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 28 other files (scripts, references) in skills/herdr-agent of luongnv89/skills.

  • SKILL.md
  • docs/README.md
  • evals/evals.json
  • references/context-succession.md
  • references/delivery-and-waiting.md
  • references/edge-cases.md
  • references/final-report.md
  • references/fleet-monitoring.md
  • references/help-request.md
  • references/herdr-recipes.md
  • references/launch-profile.md
  • scripts/badge.py
  • scripts/broadcast.sh
  • scripts/fleet_status.py
  • scripts/launch_profile.py
  • scripts/next_grid_split.py
  • scripts/preflight_send.py
  • … and 12 more

Open the folder on GitHubat commit 891c720

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Works with

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Questions about Herdr Agent

What does Herdr Agent do?

Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; help lists every operation. Herdr Agent is an agent skill from luongnv89/skills. Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; help lists every operation.

When should I use Herdr Agent?

Herdr Agent fits situations like: non-Herdr terminals; tasks that involve Subagents.

How do I install Herdr Agent in Claude Code?

Run `npx skills add luongnv89/skills --skill herdr-agent -a claude-code`. Or copy the skill folder (skills/herdr-agent in luongnv89/skills) into .claude/skills/herdr-agent in your project. Claude Code loads it when a task matches its description.

How do I install Herdr Agent in Codex?

Run `npx skills add luongnv89/skills --skill herdr-agent -a codex`. Or copy the skill folder (skills/herdr-agent in luongnv89/skills) into .agents/skills/herdr-agent in your project. Codex loads it when a task matches its description.

Can I use Herdr Agent 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 luongnv89/skills --skill herdr-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/herdr-agent, .gemini/skills/herdr-agent, .github/skills/herdr-agent and .opencode/skills/herdr-agent in your project.

What does Herdr Agent need to run?

Going by SKILL.md and its folder, Herdr Agent needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; A Bash shell. Compatibility (from SKILL.md): Requires herdr 0.9.0 or later on PATH and a running Herdr server (`herdr status`) for every operation except `help`, which runs no herdr command. Default same-kind launches also require `pane process-info` to return full argv; `--without flags` explicitly opts out..

Does Herdr Agent 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 Herdr Agent 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Herdr Agent use?

Herdr Agent is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Herdr Agent use?

About 4.8k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 15k tokens, read only when the agent opens those files.

What are the alternatives to Herdr Agent?

Skills that share tags, products or a category with Herdr Agent: Agent Deck (asheshgoplani/agent-deck, 1k stars), Clawteam (win4r/ClawTeam-OpenClaw, 1.5k stars), Multi Agent (shibing624/agentica, 352 stars) and Claude Code Delegation (XiaomiMiMo/MiMo-Code, 14k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Herdr Agent?

luongnv89 (a GitHub user) maintains it in luongnv89/skills, which has 131 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 9, 2026.

Source: luongnv89/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.