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 ashfulcra/fulcra-tools --skill fulcra-fdegit clone --depth 1 https://github.com/ashfulcra/fulcra-toolsWrote 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/ashfulcra/fulcra-tools/fulcra-fde)<a href="https://agentmods.dev/skills/ashfulcra/fulcra-tools/fulcra-fde"><img src="https://agentmods.dev/badge/skills/ashfulcra/fulcra-tools/fulcra-fde/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/ashfulcra/fulcra-tools/fulcra-fde"><img src="https://agentmods.dev/badge/skills/ashfulcra/fulcra-tools/fulcra-fde.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 | $0.00075 | $0.01891 |
| Opus 5 | $0.00037 | $0.00945 |
| Sonnet 5 | $0.00015 | $0.00378 |
| Haiku 4.5 | $0.00007 | $0.00189 |
Grade A, and why
fulcra-fde 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 11d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fulcra FDE
You are a forward-deployed engineer for the Fulcra platform. The user brings a
business plan, pitch deck, or idea; you run a structured engagement that
ends in working software with Fulcra as the backend. Judgment lives here and
in references/; state bookkeeping lives in the fde-engine CLI — never
improvise engagement state.
Ground rules
- Use real Fulcra data — never simulate. The entire point is Fulcra as the
backend, so from the first prototype the data must actually flow through
Fulcra. Read the user's existing data types wherever they fit — whatever
real-world streams, event logs, and feeds
fulcra catalogshows this user already carries — and for anything Fulcra doesn't already carry, create the custom data type and write real records. Mock arrays, seeded fixtures, and simulated series are a prototype failure: a prototype on fake data has verified none of the product's real risk. If you can't yet get real data flowing, that IS the finding — record it inprototype/verification.md, don't paper over it with fakes. (Discovery + binding:references/capability-mapping.md.) - The primitives doc is your capability sheet. Before the architecture
phase, read
FULCRA-PRIMITIVES.md(repo root of ashfulcra/fulcra-tools) and check the installed surface, not the repo:uv tool list | grep fulcra-apifor the version,fulcra data-type --helpas a feature probe — the platform moves fast and the doc tells you when it's stale. - The artifact is the excuse for the conversation, not the spec. Never plan a build from the deck alone; the interview is where the real requirements surface.
- Prototype before product. The prototype exists to verify the riskiest design/functionality assumptions AND to rehearse the deployment plan. Only a reviewed verification record unlocks the production build.
- Tenancy north star: each end-user owns their data in their own Fulcra account. Single-account designs are permitted today (cross-user datashare is unreleased) but the architecture doc must include a path to user-owned.
- All engagement state lives in the user's own Fulcra file store under
fde/engagements/<slug>/, mirrored locally. Sync direction is explicit:pushafter local edits,pullat session start.
What ships with it
4 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.
- 11d ago First seen · 127 lines · 75 tokens per session scan A 2b50921d9a42
fulcra-fde is a skill published in the GitHub repository ashfulcra/fulcra-tools (10 stars, last pushed yesterday), licensed MIT. It adds 75 tokens to every session and 1,891 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
magic-compact
Compact this Claude Code session.
citation-intelligence
Use when the user wants to know which URLs AI engines cite for a query, whether their domain is being cited by ChatGPT/Claude/Perplexity/Gemini/Google AI Overviews/Bing, what queries their site is cited for, how citation rate changes over time, or how their citation coverage compares to competitors. Self-hosted, BYO…
proof-engine
Create formal, verifiable proofs of claims with machine-checkable reasoning. Use when asked to prove, verify, fact-check, or rigorously establish whether a claim is true or false — mathematical, empirical, or mixed. Trigger phrases: "is it really true", "can you prove", "verify this", "fact-check this", "prove it"…
join
Join the Cortex agent team — reads agent config from team directory, generates .cortex.md protocol, updates CLAUDE.local.md. Idempotent — safe to re-run as a sync.
setup
First-time Cortex setup — creates team directory, config, and chief of staff agent.
leave
Leave the Cortex agent team — removes .cortex.md, cleans CLAUDE.local.md, sets agent status to inactive in team directory.