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 receptron/mulmoterminal --skill actions-firebasegit clone --depth 1 https://github.com/receptron/mulmoterminalWrote 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/receptron/mulmoterminal/actions-firebase)<a href="https://agentmods.dev/skills/receptron/mulmoterminal/actions-firebase"><img src="https://agentmods.dev/badge/skills/receptron/mulmoterminal/actions-firebase/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/receptron/mulmoterminal/actions-firebase"><img src="https://agentmods.dev/badge/skills/receptron/mulmoterminal/actions-firebase.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 | $0.00034 | $0.00927 |
| Opus 5.5 | $0.00014 | $0.00371 |
| Sonnet 5.5 | $0.00007 | $0.00185 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
blueprint-from-collection-actions 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 19d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Actions and ingests, as features (Firebase)
Read .blueprint/actions.json (written with the spec, and agreed when the spec was approved). If it does not exist, the
source had no actions or ingests: stop. Each entry names an action (books.actions.tidy) or an ingest (books.ingest),
what it was (kind) and what was decided (decision). The original instructions are in
.blueprint/source/collections/<slug>/templates/.
For every feature, build it as below, unless an earlier step already built it because a must-have needed it: then
check it against its entry and give it its test here instead of building it a second time.
- mutate — a button on the record's screen that makes the change its
setnames. Itsrequireis enforced by the security rules (or a callable function when the rules cannot express it), not only by the screen. - chat / agent — read the template: it says what the agent was asked to do. Build that as the app's own logic. A
step that genuinely needs a language model is a callable Cloud Function (
onCall({ enforceAppCheck: true }, …)) that calls the Claude API with@anthropic-ai/sdk; the key is a Secret Manager secret (defineSecret("ANTHROPIC_API_KEY")), never in the client or the repository. Never ask for or handle the key's value: if the secret is not set, ask the person through the blueprint question tool to runfirebase functions:secrets:set ANTHROPIC_API_KEYthemselves (for the dev and the production project), and wait for them. - ingest (rss / atom / http-json) — a scheduled function (
onSchedule) on the ingest's schedule that fetches the source, maps each item as the ingest'smapsays, and writes records by theidFromit names withset, never duplicating. An ingest of kindagentis built like an agent action.
Tests in test/blueprint/actions.spec.ts, one per feature, each with the entry's name in the title of its it(…) /
test(…) (it("books.actions.tidy: summarises", …)) — with it / test imported from vitest in that file (import { it } from "vitest"); the check reads titles only from
calls to those imports, so a global it, a helper of the same name, a comment or a title built at run time does not count, and neither does a describe(…) name (it("tidy") inside
describe("books.actions") is not titled books.actions.tidy: write the whole name in every test's own title) —
against the emulators: do the action as a signed-in user and read back what changed, and check that someone who must not
do it is refused. Never call the network in a test: the model call and the fetch go through clients the test replaces
with stand-ins.
For every manual: a section in README.md whose heading names the entry (## books.actions.tidy) and which says, step
by step, what a person does instead.
Done when the check passes: .blueprint/actions.json matches the source, every feature has a test titled with its
name, every manual has a README heading naming it, and emulator-test.sh actions passes.
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.
- 19d ago Changed · +2 lines 569db1d701d2
- 20d ago Changed · +1 lines 5defce13cd6f
- 21d ago First seen · 47 lines · 34 tokens per session scan A 731fe74fa54a
blueprint-from-collection-actions is a skill published in the GitHub repository receptron/mulmoterminal (243 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 927 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-30.
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