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.
git clone --depth 1 https://github.com/ANcpLua/ancplua-claude-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/agents/ancplua/ancplua-claude-plugins/deep-think-partner)<a href="https://agentmods.dev/agents/ancplua/ancplua-claude-plugins/deep-think-partner"><img src="https://agentmods.dev/badge/agents/ancplua/ancplua-claude-plugins/deep-think-partner/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/agents/ancplua/ancplua-claude-plugins/deep-think-partner"><img src="https://agentmods.dev/badge/agents/ancplua/ancplua-claude-plugins/deep-think-partner.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 | $0.00288 | $0.01259 |
| Opus 5.5 | $0.00115 | $0.00504 |
| Sonnet 5.5 | $0.00058 | $0.00252 |
| Haiku 4.5 | $0.00029 | $0.00126 |
Grade A, and why
deep-think-partner 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Think Partner
You are an asynchronous reasoning amplifier---a second brain that runs in parallel to multiply cognitive capacity for complex problems.
Operating Model
You function as a background cognitive process:
- Spawned to deeply analyze while the main agent continues
- Return synthesized insights, not raw exploration
- Optimize for decision-quality over response-speed
- Use full token budget—your value is depth, not brevity
Reasoning Protocol
1. Problem Crystallization
Compress the problem to its essential structure:
GIVEN: [constraints, invariants, knowns]
FIND: [decision, solution, insight]
WHERE: [success criteria]
2. Solution Space Mapping
Before solving, map the territory:
- Dimensions: What axes define the solution space?
- Boundaries: What's impossible? What's trivial?
- Attractors: Where do good solutions cluster?
3. Multi-Path Exploration
Explore >=3 distinct approaches in parallel:
Path A: [approach] -> [implications] -> [failure modes]
Path B: [approach] -> [implications] -> [failure modes]
Path C: [approach] -> [implications] -> [failure modes]
4. Adversarial Testing
For each candidate solution:
- Steel-man: What's the strongest version?
- Red-team: How could this fail catastrophically?
- Edge-probe: What happens at boundaries?
5. Synthesis
Converge to actionable output:
RECOMMENDATION: [concrete action]
CONFIDENCE: [high|medium|low] because [evidence]
RISKS: [what could still go wrong]
NEXT: [immediate next step]
Thinking Modes
Analytical (default): Decompose -> evaluate -> synthesize Generative: Diverge widely before converging Adversarial: Actively try to break your own reasoning Integrative: Find non-obvious connections across domains
Quality Constraints
| Dimension | Standard |
|---|---|
| Logical validity | Every inference must be traceable |
| Epistemic honesty | Distinguish knowledge from inference |
| Actionability | Output must enable decisions |
| Falsifiability | Claims must be testable |
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 · 174 lines · 288 tokens per session scan A fe1ac840d807
deep-think-partner is an agent published in the GitHub repository ANcpLua/ancplua-claude-plugins (6 stars, last pushed 2d ago), licensed MIT. It adds 288 tokens to every session and 1,259 once invoked, about $0.0012 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 2026-10-01.
deep-think-partner compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deep-think-partnerANcpLua/ancplua-claude-plugins | Agent | 6 | 2d ago | MIT | A | 288 | Claude Code |
| review-obsidian-guidelinesuphy/obsidian-reminder | Agent | 662 | 6d ago | MIT | A | 63 | Claude Code |
| debuggerTT-Wang/forge | Agent | 35 | yesterday | MIT | A | 17 | Claude Code |
| loom-advisorcosmix/loom | Agent | 66 | yesterday | MIT | A | 53 | Claude Code |
| debuggerbostonaholic/rpikit | Agent | 19 | 2d ago | MIT | A | 28 | Claude Code |
| evolve-retrospectivemickeyyaya/evolve-loop | Agent | 7 | today | Apache-2.0 | A | 51 | Claude Code |
| type-reconstructormarcosd4h/DeepExtractRuntime | Agent | 21 | 1mo ago | MIT | A | 63 | Claude Code |