queue-analysis

A workflow for placing a StockSage analysis request into a local queue without running the analysis.

In plain words
What is it for?
Use it to normalize a ticker symbol and create a durable local queue entry for later processing.
Why use it?
It records planned work while avoiding Python execution, market-data requests, and analysis workers at queue time.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/lexlapax/allbert-assist/queue-analysis
Any agent
npx skills add lexlapax/allbert-assist --skill queue-analysis
Clone the repo
git clone --depth 1 https://github.com/lexlapax/allbert-assist

Made for: Claude Code, Codex.

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 123 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00019 $0.00123
Opus 5 $0.00010 $0.00062
Sonnet 5 $0.00004 $0.00025
Haiku 4.5 $0.00002 $0.00012

Measured 2d ago against content hash e0df8d2b6c0d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

queue-analysis 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 2d 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.

apps/stocksage/priv/skills/queue-analysis/SKILL.md · 18 lines

What it actually says

Workflow

  1. Normalize the requested ticker symbol.
  2. Create a local StockSage queue row.
  3. Do not run Python, call market data, or start an analysis worker.
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. 2d ago First seen · 18 lines · 19 tokens per session scan A e0df8d2b6c0d

Subscribe to this mod's changes

queue-analysis is a skill published in the GitHub repository lexlapax/allbert-assist (11 stars, last pushed 18d ago), licensed Apache-2.0. It adds 19 tokens to every session and 123 once invoked, about $0.0001 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 2026-08-30.

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