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/qwickapps/ai-sdlc-workflowsWrote 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/commands/qwickapps/ai-sdlc-workflows/plan)<a href="https://agentmods.dev/commands/qwickapps/ai-sdlc-workflows/plan"><img src="https://agentmods.dev/badge/commands/qwickapps/ai-sdlc-workflows/plan/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/commands/qwickapps/ai-sdlc-workflows/plan"><img src="https://agentmods.dev/badge/commands/qwickapps/ai-sdlc-workflows/plan.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 | $0.00006 | $0.00699 |
| Opus 5.5 | $0.00002 | $0.00280 |
| Sonnet 5.5 | $0.00001 | $0.00140 |
| Haiku 4.5 | $0.00001 | $0.00070 |
Grade A, and why
plan 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 2mo 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quick Planning Mode
You are now in Planning Mode. Use this for quick analysis before action.
Input: $ARGUMENTS (task description, question, or problem to analyze)
Purpose
This is a lightweight planning workflow for tasks that don't need full SDLC.
Use /feature, /bug, /refactor for more structured workflows.
CRITICAL RULES
- Analyze before acting - never jump straight to implementation (see RESEARCH-DEPTH.md)
- Present options - don't assume one approach is correct
- Wait for approval - user decides the direction
- Think like architect + PM + UX designer
- When blocked or uncertain - STOP and discuss (see COMMUNICATION-PROTOCOL.md)
- Research thoroughly - use Explore agent, QwickBrain MCP (see RESEARCH-DEPTH.md)
Interactive Setup
Check if $ARGUMENTS is provided.
If $ARGUMENTS is empty, ask:
"What would you like me to plan or analyze? Please describe:
- The task or problem
- Any constraints or preferences
- What outcome you're looking for"
Wait for response before proceeding.
Planning Process
Step 1: Understand the Request
Ask yourself (and user if unclear):
- What is being asked?
- What problem does this solve?
- What are the constraints?
- What existing solutions might help? (REUSE FIRST)
Step 2: Analyze Options
For any non-trivial task, identify:
- Option A: [approach with pros/cons]
- Option B: [approach with pros/cons]
- Recommended: [which and why]
Consider:
- Complexity vs simplicity
- Breaking changes vs backwards compatibility
- Time to implement
- Risk and unknowns
Step 3: Present Plan
Format:
## Analysis
**Understanding:** [restate the request]
**Existing solutions:** [what can be reused]
## Options
### Option A: [name]
- Approach: [description]
- Pros: [list]
- Cons: [list]
### Option B: [name]
- Approach: [description]
- Pros: [list]
- Cons: [list]
## Recommendation
[Which option and why]
## Implementation Steps
1. [step 1]
2. [step 2]
3. [step 3]
---
Approve this plan to proceed, or provide feedback.
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.
- 2mo ago First seen · 129 lines · 6 tokens per session scan A bc660640127e
plan is a command published in the GitHub repository qwickapps/ai-sdlc-workflows (2 stars, last pushed 7mo ago), licensed MIT. It adds 6 tokens to every session and 699 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.