Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/vinnie357/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/vinnie357/claude-skills/delegate)<a href="https://agentmods.dev/commands/vinnie357/claude-skills/delegate"><img src="https://agentmods.dev/badge/commands/vinnie357/claude-skills/delegate.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00784 |
| Opus 5 | $0.00008 | $0.00392 |
| Sonnet 5 | $0.00003 | $0.00157 |
| Haiku 4.5 | $0.00002 | $0.00078 |
Grade A, and why
delegate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Run altana delegate to send a task to a single named harness preset and return the structured result.
What it does:
- Invokes
altana delegate <harness> "<task>"with any supplied flags via Bash. - For long-running agents (timeout_s > 300 or when
--writeis present) runs the command in the background and streams the result when complete. - Parses the JSON object from stdout.
- Surfaces a human-readable summary: harness name, status, duration, response text (trimmed to key sections), and log path for debugging.
- On non-
donestatus, explains the failure mode and points to the log file.
Arguments:
<harness>— name of a configured harness preset (seealtana listto enumerate presets).<task>— the prompt string to delegate. Wrap in quotes if it contains spaces.--prompt <template>— optional named prompt template from[prompt.<name>]in config; wraps the task before dispatch.--write— grant the agent write access to the working directory inside the container (awman executor only).
JSON result fields:
| Field | Type | Description |
|---|---|---|
harness |
string | Harness name used |
status |
string | done | timeout | crash | missing_sentinel |
duration_s |
float | Wall-clock seconds |
log_path |
string | Full subprocess log path |
response |
string or null | Agent response (sentinel stripped); null on non-done |
Status meanings:
done— agent exited 0 and emitted the completion sentinel;responseis populated.missing_sentinel— agent exited 0 but did not emit the sentinel; checklog_path.crash— agent exited non-zero or failed to spawn; checklog_path.timeout— agent exceeded the configuredtimeout_s; checklog_pathfor partial output.
If altana is not installed:
Install altana (see its README — it is a Zig CLI built with zig 0.16). After building, place the binary on your PATH or invoke via mise exec -- zig-out/bin/altana.
Examples:
/delegate my-claude "explain the failing test in src/parser_test.zig"
/delegate critique-harness "review src/main.zig" --prompt critique
/delegate coding-agent "add error handling to the fetch function" --write
Task instructions:
Resolve the argument string: the first positional token is <harness>, the remaining text up to the first -- flag is <task>. Reconstruct any --prompt <template> or --write flags from the parsed argument, using space-separated form.
Run: altana delegate "<harness>" "<task>" [flags]
Parse the JSON result. Present:
- A one-line status line:
harness: <name> | status: <status> | duration: <duration_s>s - If
status == "done": theresponsecontent (show## Answer,## Evidence,## Confidencesections). - If
status != "done": the failure mode explanation and thelog_pathto inspect.
Load /altana:altana for protocol and config reference before running.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 64 lines · 15 tokens per session scan A 54a26cf4b71d
delegate is a command published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 784 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.