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 jumppad-labs/spektacular --skill spek-plangit clone --depth 1 https://github.com/jumppad-labs/spektacularWrote 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/jumppad-labs/spektacular/spek-plan)<a href="https://agentmods.dev/skills/jumppad-labs/spektacular/spek-plan"><img src="https://agentmods.dev/badge/skills/jumppad-labs/spektacular/spek-plan/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/jumppad-labs/spektacular/spek-plan"><img src="https://agentmods.dev/badge/skills/jumppad-labs/spektacular/spek-plan.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00013 | $0.02166 |
| Opus 5 | $0.00006 | $0.01083 |
| Sonnet 5 | $0.00003 | $0.00433 |
| Haiku 4.5 | $0.00001 | $0.00217 |
Grade A, and why
spek-plan 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 2d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version check first. Before running any other command, run
go run . version check.
- On
status: "match", continue with the skill and produce no version-related output.- On
"mismatch"or"missing", the installed Spektacular files are out of date: relay the response'sactionmessage to the user, ask them to re-rungo run . init <agent>, and wait for their decision before continuing.- Never modify or re-install any installed files yourself — refreshing the installation is always an explicit, user-initiated re-run of init.
STOP. Read this before running any command below. A single successful CLI call — including the very first
plan new— is NOT task completion. It is not a milestone to report back to the user. It is one step out of many in a workflow that you must keep driving, turn after turn, without stopping, until the CLI itself tells you the workflow is finished. If you find yourself about to say "successfully completed" or summarize results after callingplan neworplan gotoeven once, you are wrong — go back and read theinstructionfield you just received, do what it says, and callgotoagain.
What this skill does
This skill drives a multi-step interactive workflow that produces a complete implementation plan — the assembled plan.md, context.md, and research.md documents committed to the plan store — from an existing spec. The workflow is owned by the go run . CLI, not by you — the CLI is the state machine and you are the executor, and the CLI (not the filesystem) is how you reach every plan document.
On each turn, the CLI returns JSON containing an instruction field. That instruction describes exactly one step (e.g. discovery, data structures, phases, testing approach, walkthrough, …). You must:
- Read the
instructioncarefully. - Perform the step — this may mean researching the codebase, spawning subagents, interviewing the user, or committing a plan document to the store.
- When the step is complete, run the
gotocommand named at the bottom of the instruction to advance the state machine. - Read the next
instructionfrom the new JSON response and repeat.
This is a loop. Do not stop after the first step. Keep looping — step → goto → next instruction → step — until a returned instruction tells you the workflow is finished. Only then should you report completion to the user.
Concretely: do not stop after plan new. That command only starts the workflow — it returns the first instruction (the overview step), not a finished plan. Seeing a clean JSON response with no error is not a signal to stop; it is the signal to keep going. Reporting success, summarizing "plan initialized," or handing control back to the user at this point is the single most common way this skill is executed incorrectly — do not do it.
The workflow ends with a mandatory walkthrough review. After the three documents are committed to the store, the CLI renders the walkthrough step: walk the user through the committed plan section by section, apply any requested changes immediately through go run . plan file write, and only advance to finished once the user gives an explicit affirmative answer to a direct closing question. Committed documents are not completion — the workflow is finished, and the plan approved, only after the user signs off during the walkthrough and the finished step has run.
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.
- 2d ago Changed e5b8bb93f63c
- 12d ago First seen · 78 lines · 13 tokens per session scan A 6d705455bd1d
spek-plan is a skill published in the GitHub repository jumppad-labs/spektacular (20 stars, last pushed 2d ago), licensed Apache-2.0. It adds 13 tokens to every session and 2,166 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 2026-08-30.
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