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 richfrem/agent-plugins-skills --skill discovery-planninggit clone --depth 1 https://github.com/richfrem/agent-plugins-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/skills/richfrem/agent-plugins-skills/discovery-planning)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/discovery-planning"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/discovery-planning.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00092 | $0.05120 |
| Opus 5 | $0.00046 | $0.02560 |
| Sonnet 5 | $0.00018 | $0.01024 |
| Haiku 4.5 | $0.00009 | $0.00512 |
Grade A, and why
discovery-planning 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 4d 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 — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architectural patterns adapted from obra/superpowers (MIT) https://github.com/obra/superpowers
Dashboard Intercept
Before doing anything else, silently check for exploration/exploration-dashboard.md.
- If the file EXISTS:
- Read the file and check the status. If status is
Complete, proceed standalone. - If status is
In ProgressorTBD:- Check for the presence of the
<ORCHESTRATOR_DISPATCH>tag in the immediate context. - If the tag is PRESENT:
- Extract and verify the
authorized_skill,phase_number, andexpected_outputattributes from the<ORCHESTRATOR_DISPATCH>tag. - If
authorized_skillmatches "discovery-planning" ANDphase_numbermatches the dashboard phase:- Proceed with this skill's logic. (You are authorized by the orchestrator).
- Note: The orchestrator manages dispatch token lifecycle. This tag is valid for the current phase only — it becomes stale once the orchestrator advances the dashboard in Block 6.
- If verification fails (mismatched name or stale phase):
- Stop immediately. Announce: "Orchestrator dispatch verification failed. Returning to dashboard."
- Return control. Invoke skill:
exploration-workflow. Stop generating output.
- Extract and verify the
- If the tag is ABSENT or malformed:
- Stop immediately. Do not continue.
- Announce: "It looks like you have an active Exploration Session. Let me take you back to your session dashboard."
- Return control to the orchestrator. Invoke skill:
exploration-workflow. Stop generating output from this skill.
- Check for the presence of the
- Read the file and check the status. If status is
- If the file DOES NOT exist: Proceed standalone.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 425 lines · 92 tokens per session scan A a53694071296
discovery-planning is a skill published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 5,120 once invoked, about $0.0005 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 skills, from other repositories
review-offered-task
Review a task that has been offered to you and decide whether to accept or reject it.
close-issue
Close a GitHub or GitLab issue with a summary comment.
implement-issue
Implement a GitHub issue or GitLab issue and create a PR/MR.
gh-create-issue
Use when filing a GitHub issue for a bug, feature, audit, review finding, or investigated piece of work.
worktrees
Use when fanning several tickets into parallel branches and git worktrees, with related tickets grouped together.
ticket-rebuild
Use when rebuilding a bloated tracker item whose epic or Jira ticket hard-codes implementation, restates a spec, or cites counts and line numbers.