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 alex-jb/shadow-perception-mcp --skill shadow-perception-tradergit clone --depth 1 https://github.com/alex-jb/shadow-perception-mcpWrote 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/alex-jb/shadow-perception-mcp/shadow-perception-trader)<a href="https://agentmods.dev/skills/alex-jb/shadow-perception-mcp/shadow-perception-trader"><img src="https://agentmods.dev/badge/skills/alex-jb/shadow-perception-mcp/shadow-perception-trader/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/alex-jb/shadow-perception-mcp/shadow-perception-trader"><img src="https://agentmods.dev/badge/skills/alex-jb/shadow-perception-mcp/shadow-perception-trader.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 | $0.00099 | $0.01173 |
| Opus 5 | $0.00049 | $0.00587 |
| Sonnet 5 | $0.00020 | $0.00235 |
| Haiku 4.5 | $0.00010 | $0.00117 |
Grade A, and why
shadow-perception-trader 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 8d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shadow Perception — Trader vertical
Five-voice deterministic pre-submit council for trading tickets. Deterministic — no LLM call in the verdict path.
When to use
The user's request is any variant of:
- "Should I submit this order?"
- "Am I over-concentrated in TSLA?"
- "Is this position size Kelly-safe?"
- "Fat-finger check on this qty?"
- "Reg BI OK for retirement account?"
Or the user pastes a JSON trade ticket and asks for pre-submit review.
What it does
shadow_perception_scan(file_path)— parses a JSON ticket. Computes notional, Kelly fraction (from p_win + R:R), sector/single-name projected exposure, qty ratio vs typical.shadow_perception_council(observation)— 5-voice council:- Kelly — position ≤ max_kelly_cap? Negative Kelly = BLOCK.
- Risk — stop_loss set? MKT BUY = REWORK.
- Concentration — sector cap 40%, single-name cap 25%. Projected exposure post-trade must be within.
- Fat-Finger — qty vs typical. 3× = REWORK, 10× = BLOCK (Knight Capital 2012).
- Reg BI — retirement account + high-risk pattern = REWORK requiring supervisor sign-off per SEC Reg BI §240.15l-1(a)(2)(ii).
shadow_perception_attest(observation, verdict)— Ed25519 signs. Attach to broker submission or audit log.
The named invariants
- Never emits a direction. The council receives side (BUY / SELL) as input. It decides only fund / skip / reduce, never direction. Aligned with shadow-mentor trader-pack v0.2
shadow_size_positioncontract. - Fat-Finger BLOCK is unconditional at 10×. Knight Capital $440M loss 2012 is the historical anchor.
- Reg BI voice only fires on
reg_bi_client_profile: "retirement". Explicitly opt-in to avoid false positives on trading accounts. - Kelly voice BLOCKs on negative Kelly. No pretending an edge exists when p_win × R:R doesn't clear break-even.
Ticket JSON contract (minimal)
{
"symbol": "TSLA",
"side": "BUY",
"qty": 500,
"price": 245.50,
"order_type": "MKT",
"stop_price": null,
"take_profit": null,
"bankroll_usd": 25000,
"typical_qty_for_ticker": 50,
"sector": "Consumer Discretionary",
"portfolio_sector_exposure_usd": { "Consumer Discretionary": 3400 },
"single_name_exposure_usd": { "TSLA": 2200 },
"kelly_p_win": 0.55,
"kelly_avg_win_pct": 0.05,
"kelly_avg_loss_pct": 0.025,
"max_kelly_cap": 0.25,
"reg_bi_client_profile": "retirement"
}
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.
- 8d ago First seen · 103 lines · 99 tokens per session scan A eb95cc1c4779
shadow-perception-trader is a skill published in the GitHub repository alex-jb/shadow-perception-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 99 tokens to every session and 1,173 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 2026-08-31.
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