BF AgentCanary
Cross-asset market intelligence API for AI agents. 130+ endpoints across macro regime detection, risk scoring, trading signals (IGNITION/ACCUMULATION/DISTRIBUTION/CAPITULATION), whale alerts, funding arbitrage, orderbook analytics, live derivatives (cross-exchange open interest, perp liquidations with long/short split), DeFi yields/PE ratios, BTC options (max pain, skew), central bank balance sheets, narrative crowding scores, sector rotation, Hindenburg omen, CAPE ratio, scenario probabilities, BTC ETF flows, geopolitical risk, mean reversion signals, institutional positioning (13F, short interest, CFTC COT), Reddit/X sentiment, and 4× daily AI market briefs (Radar 03:15, Signal 09:15, Pulse 15:15, Wrap 21:15 UTC). Wallet-based auth, USDC/USDT on any major EVM chain (Base, Ethereum, Arbitrum, Optimism, Polygon). Use when an agent needs macro regime context, risk assessment, position sizing guidance, market structure data, derivatives positioning, whale monitoring, news sentiment, DeFi intelligence, options flow, or institutional positioning. API-only — no local execution, no filesystem access, no secrets in prompt.
As a process F 40/100 · Will not run — References files that are not bundled: references/endpoints.md
How to improve
- Shorten the description to 1024 characters.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1133 chars, limit 1024 - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
missing-refreference to a missing file: references/endpoints.md - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 40/100
- 0Tools and files. 1 referenced file(s) missing: references/endpoints.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 26 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3004 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1133: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 15 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.