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.
npx skills add legendtkl/agentic-skill-router --skill skill-141git clone --depth 1 https://github.com/legendtkl/agentic-skill-routerWrote 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/skills/legendtkl/agentic-skill-router/skill-141)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-141"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-141/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-141"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-141.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00024 | $0.00728 |
| Opus 5 | $0.00012 | $0.00364 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
skill-141 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirements for Outputs
General Guidelines
PDDL Files
- Domain files must define actions with time constraints and resources.
- Problem files should specify deadlines for tasks.
- Schedules must follow sequential constraints.
Scheduler Behavior
- Scheduling must complete within a specified timeout.
- If no schedule exists, return an empty schedule or an explicit failure flag.
PDDL Scheduling Skills
1. Load Scheduling Domain and Problem
load-scheduling-problem(domain_path, problem_path)
Description:
Loads a PDDL domain file and problem file for scheduling tasks, creating a scheduling problem instance.
Parameters:
domain_path(str): Path to the PDDL domain file.problem_path(str): Path to the PDDL problem file.
Returns:
scheduling_problem: A scheduling problem object.
Example:
scheduling_problem = load_scheduling_problem("scheduling_domain.pddl", "tasks_to_schedule.pddl")
Notes:
- Uses
unified_planning.io.PDDLReader. - Raises an error if parsing fails.
2. Generate Schedule
generate-schedule(scheduling_problem)
Description: Generates a schedule for the specified planning problem based on task timings and deadlines.
Parameters:
scheduling_problem: A scheduling problem instance.
Returns:
schedule: A list of scheduled tasks with timing.
Example:
schedule = generate_schedule(scheduling_problem)
Notes:
- Uses
unified_planning.shortcuts.Scheduler. - Returns None if no schedule can be found.
3. Save Schedule
save-schedule(schedule, output_path)
Description: Writes the generated schedule to a file in a specified format suitable for scheduling applications.
Parameters:
schedule: A list of scheduled tasks.output_path(str): Path where the schedule will be saved.
Example:
save_schedule(schedule, "scheduled_tasks.txt")
Notes:
- Utilizes a specialized file writer for scheduling formats.
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.
- 7d ago First seen · 125 lines · 24 tokens per session scan A b92e3d1a9dba
skill-141 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 728 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.
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