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 agentmods add skills/bjorn-ingmanson/thefroject-plugins/parallel-analyzenpx skills add bjorn-ingmanson/thefroject-plugins --skill parallel-analyzegit clone --depth 1 https://github.com/bjorn-ingmanson/thefroject-pluginsWrote 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/bjorn-ingmanson/thefroject-plugins/parallel-analyze)<a href="https://agentmods.dev/skills/bjorn-ingmanson/thefroject-plugins/parallel-analyze"><img src="https://agentmods.dev/badge/skills/bjorn-ingmanson/thefroject-plugins/parallel-analyze.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.00599 |
| Opus 5 | $0.00023 | $0.00300 |
| Sonnet 5 | $0.00009 | $0.00120 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
parallel-analyze 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 5d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Analyze
Split the same task across parallel agents (one per target), then merge their results into a single report.
When to Use This Pattern
- The same task applies to multiple independent targets (audit 5 modules, review 8 files, analyze 12 endpoints)
- Each target can be processed independently
- You need a combined summary, not just individual results
Process
Phase 1: Map (Identify Targets)
List all targets. For each target, confirm:
- It can be processed independently (no cross-dependencies)
- The same prompt and criteria apply to all targets
- The expected output format is consistent
Phase 2: Map (Dispatch)
Spawn one agent per target (or per batch of small targets). All agents:
- Receive the same instructions and criteria
- Get their specific target(s) as context
- Use the same restricted tool set
- Return results in the same format
Launch all agents in parallel (multiple Agent calls in one message).
Phase 3: Reduce (Merge)
When all agents return:
- Collect all results
- Deduplicate findings that appear across multiple targets
- Rank by severity or importance
- Produce a single summary with:
- Overall assessment
- Per-target highlights (only notable items, not everything)
- Cross-cutting patterns (issues that appear in 3+ targets)
- Recommended actions, prioritized
Example
Task: "Security audit all API route handlers"
Map: 6 route files, each gets its own agent with the same security checklist. Reduce: Merge into one report. Flag patterns ("4 of 6 routes missing rate limiting") over individual findings.
Sizing Guide
| Targets | Strategy |
|---|---|
| 1-2 | Do not use parallel-analyze. Just do the work. |
| 3-6 | One agent per target. Ideal range. |
| 7-15 | Batch targets into 3-5 groups. One agent per group. |
| 15+ | Batch into 5-7 groups. Consider if the task scope is too broad. |
Rules
- All map agents must use the same output format. Define it in the prompt.
- Cap at 7 parallel agents. More than that and the reduce phase becomes unwieldy.
- The reduce step is your job, not another agent's. You have the full picture.
- If one agent fails or returns poor results, re-run just that one.
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.
- 5d ago First seen · 78 lines · 45 tokens per session scan A 821e48b637fa
parallel-analyze is a skill published in the GitHub repository bjorn-ingmanson/thefroject-plugins (1 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 599 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…