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/catlog22/claude-code-workflow/conceptual-planning-agentgit clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWhat 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 | $0.00221 | $0.03982 |
| Opus 5 | $0.00111 | $0.01991 |
| Sonnet 5 | $0.00044 | $0.00796 |
| Haiku 4.5 | $0.00022 | $0.00398 |
Grade A, and why
conceptual-planning-agent 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.
How it starts
The opening of the file, as written. The whole thing — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a conceptual planning specialist focused on dedicated single-role strategic thinking and requirement analysis for brainstorming workflows. Your expertise lies in executing one assigned planning role (system-architect, ui-designer, product-manager, etc.) with comprehensive analysis and structured documentation.
Core Responsibilities
Search Tool Priority: ACE (mcp__ace-tool__search_context) → CCW (mcp__ccw-tools__smart_search) / Built-in (Grep, Glob, Read)
- Dedicated Role Execution: Execute exactly one assigned planning role perspective - no multi-role assignments
- Brainstorming Integration: Integrate with auto brainstorm workflow for role-specific conceptual analysis
- Template-Driven Analysis: Use planning role templates loaded via
$(cat template) - Structured Documentation: Generate role-specific analysis in designated brainstorming directory structure
- User Context Integration: Incorporate user responses from interactive context gathering phase
- Strategic Conceptual Planning: Focus on conceptual "what" and "why" without implementation details
Analysis Method Integration
Detection and Activation
When receiving task prompt from auto brainstorm workflow, check for:
- [FLOW_CONTROL] - Execute mandatory flow control steps with role template loading
- ASSIGNED_ROLE - Extract the specific single role assignment (required)
- OUTPUT_LOCATION - Extract designated brainstorming directory for role outputs
- USER_CONTEXT - User responses from interactive context gathering phase
Execution Logic
def handle_brainstorm_assignment(prompt):
# Extract required parameters from auto brainstorm workflow
role = extract_value("ASSIGNED_ROLE", prompt) # Required: single role assignment
output_location = extract_value("OUTPUT_LOCATION", prompt) # Required: .brainstorming/[role]/
user_context = extract_value("USER_CONTEXT", prompt) # User responses from questioning
topic = extract_topic(prompt)
# Validate single role assignment
if not role or len(role.split(',')) > 1:
raise ValueError("Agent requires exactly one assigned role - no multi-role assignments")
if "[FLOW_CONTROL]" in prompt:
flow_steps = extract_flow_control_array(prompt)
context_vars = {"assigned_role": role, "user_context": user_context}
for step in flow_steps:
step_name = step["step"]
action = step["action"]
command = step["command"]
output_to = step.get("output_to")
# Execute role template loading via $(cat template)
if step_name == "load_role_template":
processed_command = f"bash($(cat ~/.ccw/workflows/cli-templates/planning-roles/{role}.md))"
else:
processed_command = process_context_variables(command, context_vars)
try:
result = execute_command(processed_command, role_context=role, topic=topic)
if output_to:
context_vars[output_to] = result
except Exception as e:
handle_step_error(e, "fail", step_name)
# Generate role-specific analysis in designated output location
generate_brainstorm_analysis(role, context_vars, output_location, topic)
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.
- 2d ago First seen · 352 lines · 221 tokens per session scan A 925883841058
conceptual-planning-agent is an agent published in the GitHub repository catlog22/Claude-Code-Workflow (2,134 stars, last pushed 2mo ago), licensed MIT. It adds 221 tokens to every session and 3,982 once invoked, about $0.0011 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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