alpha-squad

alpha-squad is a skill for Codex from DeevsDeevs/agent-system. It costs 72 tokens per session (312 once invoked), scanned A, original, Apache-2.0.

A workflow for generating investment-market hypotheses from several viewpoints, including company accounts, trading flows, business networks, market mechanics, and cause-and-effect checks.

In plain words
What is it for?
Use it to create and combine market hypotheses, either through one named analyst role or through several roles working in parallel.
Why use it?
It helps reduce one-sided reasoning by requiring each idea to explain its mechanism, who is affected, what constraint drives it, and when it may stop working.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to create and combine market hypotheses, either through one named analyst role or through several roles working in parallel.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/deevsdeevs/agent-system/alpha-squad
Install

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.

Any agent
npx skills add DeevsDeevs/agent-system --skill alpha-squad
Clone the repo
git clone --depth 1 https://github.com/DeevsDeevs/agent-system

Made for: Codex.

Wrote 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.

agentmods badge for alpha-squad

README.md
[![agentmods](https://agentmods.dev/badge/skills/deevsdeevs/agent-system/alpha-squad/github.svg)](https://agentmods.dev/skills/deevsdeevs/agent-system/alpha-squad)
Your own site
<a href="https://agentmods.dev/skills/deevsdeevs/agent-system/alpha-squad"><img src="https://agentmods.dev/badge/skills/deevsdeevs/agent-system/alpha-squad/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.

agentmods 80×15 button for alpha-squad

Your own site · 80×15
<a href="https://agentmods.dev/skills/deevsdeevs/agent-system/alpha-squad"><img src="https://agentmods.dev/badge/skills/deevsdeevs/agent-system/alpha-squad.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 312 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.00312
Opus 5.5 $0.00029 $0.00125
Sonnet 5.5 $0.00014 $0.00062
Haiku 4.5 $0.00007 $0.00031

Measured 1mo ago against content hash f2f769e48513, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

alpha-squad 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 1mo 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.

alpha-squad/SKILL.md · 26 lines

What it actually says

Alpha Squad

Use this skill when the user wants market hypotheses generated from complementary lenses.

Role Map

  • fundamentalist -> agents/fundamentalist.md
  • vulture -> agents/vulture.md
  • network-architect -> agents/network-architect.md
  • book-physicist -> agents/book-physicist.md
  • causal-detective -> agents/causal-detective.md

Workflow

  1. Read README.md and enforce mechanism-first reasoning.
  2. If the user specified one role, spawn exactly that role with agent_type and task context.
  3. If no role was specified, spawn all five roles in parallel and ask each for 1-3 high-conviction hypotheses.
  4. Use wait to gather results, then synthesize a single hypothesis slate.
  5. Ensure every proposed hypothesis includes counterparty, constraint, decay horizon, and mechanism sketch.
  6. If confidence is weak or confounding is likely, run a follow-up pass with causal-detective before presenting final output.
Files

What ships with it

7 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.

Changes

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.

  1. 1mo ago First seen · 26 lines · 72 tokens per session scan A f2f769e48513

Subscribe to this mod's changes

alpha-squad is a skill published in the GitHub repository DeevsDeevs/agent-system (41 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 312 once invoked, about $0.0003 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 2026-08-30.

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