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 sequenzia/agent-alchemy --skill deep-analysisgit clone --depth 1 https://github.com/sequenzia/agent-alchemyWrote 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/sequenzia/agent-alchemy/deep-analysis)<a href="https://agentmods.dev/skills/sequenzia/agent-alchemy/deep-analysis"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/deep-analysis/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/sequenzia/agent-alchemy/deep-analysis"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/deep-analysis.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 | $0.00052 | $0.06158 |
| Opus 5.5 | $0.00021 | $0.02463 |
| Sonnet 5.5 | $0.00010 | $0.01232 |
| Haiku 4.5 | $0.00005 | $0.00616 |
Grade A, and why
deep-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 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.
How it starts
The opening of the file, as written. The whole thing — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Analysis Workflow
Execute a structured exploration + synthesis workflow using Agent Teams with hub-and-spoke coordination. The lead performs rapid reconnaissance to generate dynamic focus areas, composes a team plan for review, workers explore independently, and a synthesizer merges findings with Bash-powered investigation.
This skill can be invoked standalone or loaded by other skills as a reusable building block. Approval behavior is configurable via .claude/agent-alchemy.local.md.
Settings Check
Goal: Determine whether the team plan requires user approval before execution.
-
Read settings file:
- Check if
.claude/agent-alchemy.local.mdexists - If it exists, read it and look for a
deep-analysissection with nested settings:- **deep-analysis**: - **direct-invocation-approval**: true - **invocation-by-skill-approval**: false - If the file does not exist or is malformed, use defaults (see step 4)
- Check if
-
Determine invocation mode:
- Direct invocation: The user invoked
/deep-analysisdirectly, or you are running this skill standalone - Skill-invoked: Another skill (e.g., codebase-analysis, feature-dev, docs-manager) loaded and is executing this workflow
- Direct invocation: The user invoked
-
Resolve settings:
- If settings were found, use them as-is
- If the file is missing or the
deep-analysissection is absent, use defaults:direct-invocation-approval:trueinvocation-by-skill-approval:false
- If the file exists but is malformed (unparseable), warn the user and use defaults
-
Set
REQUIRE_APPROVAL:- If direct invocation → use
direct-invocation-approvalvalue (default:true) - If skill-invoked → use
invocation-by-skill-approvalvalue (default:false)
- If direct invocation → use
-
Parse session settings (also under the
deep-analysissection):- **deep-analysis**: - **cache-ttl-hours**: 24 - **enable-checkpointing**: true - **enable-progress-indicators**: truecache-ttl-hours: Number of hours before exploration cache expires. Default:24. Set to0to disable caching entirely.enable-checkpointing: Whether to write session checkpoints at phase boundaries. Default:true.enable-progress-indicators: Whether to display[Phase N/6]progress messages. Default:true.
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.
- 1mo ago First seen · 522 lines · 52 tokens per session scan A 8bbe3313e76c
deep-analysis is a skill published in the GitHub repository sequenzia/agent-alchemy (45 stars, last pushed 4mo ago), licensed MIT. It adds 52 tokens to every session and 6,158 once invoked, about $0.0002 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.
Other skills, from other repositories
connect
Install the scoped Antigravity permission hook.
hook-template
Generate hook script from template. Use when adding a new hook, wiring a PreToolUse/PostToolUse/Stop/Notification hook, or scaffolding hook config for settings.json.
check-environment
Verify Claude, Codex, and Grok availability plus Director guidance, relay, agents, and skills. Audit optional hooks only when selected. Use after installation or when a native surface misbehaves.
test-runner
Test execution reference: framework detection (pytest/jest/vitest/go/cargo/junit) and correct run/coverage commands, plus failure-analysis steps. Use when running tests, analyzing test failures, or verifying coverage after code changes.
agents
List all available agents (core, expert, self-evolving). Use when the user asks what agents are available or runs /agents.
handoff-gemini
Delegate long-context analysis, research, and large-document summarization to Google Gemini CLI (1M-token context) via non-interactive gemini -p, preserving Claude context. Use when the user says 'use gemini'/'hand off to gemini' or a task needs 100K+ tokens of context.