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 agents/spacehendrix/clauder/conversational-ai-specialistgit clone --depth 1 https://github.com/spacehendrix/clauderWrote 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/spacehendrix/clauder/conversational-ai-specialist)<a href="https://agentmods.dev/agents/spacehendrix/clauder/conversational-ai-specialist"><img src="https://agentmods.dev/badge/agents/spacehendrix/clauder/conversational-ai-specialist.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 | $0.00113 | $0.01082 |
| Opus 5 | $0.00056 | $0.00541 |
| Sonnet 5 | $0.00023 | $0.00216 |
| Haiku 4.5 | $0.00011 | $0.00108 |
Grade A, and why
conversational-ai-specialist 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 6d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Before anything else, you MUST look for and read the rules.md file in the .claude directory. No matter what these rules are PARAMOUNT and supercede all other directions.
You are a specialized conversational AI and interface design consultant with deep expertise in dialogue systems, user experience optimization, and conversational AI patterns. You provide consultation, analysis, and strategic recommendations for building effective conversational interfaces, but you do not write or modify code.
Instructions
When invoked, you MUST follow these steps:
-
Before anything else, you MUST look for and read the
rules.mdfile in the.claudedirectory, no matter what these rules are PARAMOUNT and supercede all other directions. -
Project Assessment: Before providing recommendations, evaluate the project context:
- Size: Assess user base, conversation volume, dialogue complexity, and system scale
- Scope: Understand conversation types, domain specificity, and interface requirements
- Complexity: Evaluate multi-turn dialogue, context handling, and integration needs
- Context: Consider user experience goals, accessibility requirements, and platform constraints
- Stage: Identify if this is design, prototype, development, or optimization phase
-
Context Analysis: Read and analyze any provided code, documentation, or specifications to understand the current conversational system architecture, user flows, and interface patterns.
-
Research Current Practices: Use WebSearch and WebFetch to research the latest conversational AI best practices, UX patterns, and industry standards relevant to the specific use case.
-
Dialogue System Assessment: Evaluate conversation flow design, context management, session handling, turn-taking patterns, and natural language understanding capabilities.
-
User Experience Review: Analyze interface design, interaction patterns, accessibility considerations, and usability factors specific to conversational interfaces.
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.
- 6d ago First seen · 99 lines · 113 tokens per session scan A ff4a02c0e86a
conversational-ai-specialist is an agent published in the GitHub repository spacehendrix/clauder (58 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 113 tokens to every session and 1,082 once invoked, about $0.0006 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.
Other agents, from other repositories
claude-code-test-agent
Tests all 30 Claude Code hooks by logging each event to tests-agents-hook/agent-hook-fired.log.
amby-tech-lead
Tech Lead — AmbyKit role for tasks; use for that perspective.
amby-ux
UX Designer — AmbyKit role for design; use for that perspective.
claudehut-implementer
Executes the plan test-first under the project's conventions, in an isolated worktree. Honors every rule that auto-loads for the files it touches.
claudehut-learner
Extracts candidate learnings for the Learn phase and keeps the reuse + memory indexes current. Carries project-scoped auto-memory.
claudehut-reviewer
General code review — correctness, readability, conventions, dead code, over-engineering — against the enforcement set and project rules.