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 commands/kandil7/prprompts-flutter-generator/implementation-plangit clone --depth 1 https://github.com/Kandil7/prprompts-flutter-generatorWrote 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/kandil7/prprompts-flutter-generator/implementation-plan)<a href="https://agentmods.dev/commands/kandil7/prprompts-flutter-generator/implementation-plan"><img src="https://agentmods.dev/badge/commands/kandil7/prprompts-flutter-generator/implementation-plan.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 | $0.00017 | $0.06958 |
| Opus 5 | $0.00009 | $0.03479 |
| Sonnet 5 | $0.00003 | $0.01392 |
| Haiku 4.5 | $0.00002 | $0.00696 |
Grade A, and why
Generate Implementation 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 4d 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 — 864 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Implementation Plan
Overview
Create a comprehensive, intelligent implementation plan from PRD that includes:
- Dependency-aware task ordering (uses critical path from FEATURE_DEPENDENCIES.md)
- Sprint planning (2-week sprints, velocity-based allocation)
- Team allocation (skill-based assignment from PRD team_composition)
- Risk assessment (HIPAA/PCI-DSS/security tasks flagged)
- Maximum task detail (subtasks, code snippets, test scenarios, acceptance criteria)
- Progress tracking (TODO/IN_PROGRESS/BLOCKED/DONE states, velocity, burndown)
Output: docs/IMPLEMENTATION_PLAN.md (~850+ lines)
Step 1: Input Validation
Check for required and optional files:
# Required
ls docs/PRD.md
# Optional (enhances intelligence)
ls docs/FEATURE_DEPENDENCIES.md
ls docs/COST_ESTIMATE.md
If PRD.md missing:
❌ Error: docs/PRD.md not found
Please run:
claude create-prd
OR
claude auto-gen-prd
Then try again.
If optional files missing:
⚠️ Warning: Enhanced planning files not found
For smarter plans, run:
claude analyze-dependencies # Creates FEATURE_DEPENDENCIES.md
claude estimate-cost # Creates COST_ESTIMATE.md
Proceeding with basic plan...
Step 2: Extract Data from PRD
Read docs/PRD.md and extract:
From YAML Frontmatter:
project_name: "HealthTracker Pro"
project_type: "healthcare"
platforms: ["ios", "android", "web"]
compliance: ["hipaa", "gdpr"]
sensitive_data: ["phi", "pii"]
team_size: "5-10"
team_composition: "balanced" # junior-heavy | balanced | senior-heavy
timeline_months: 6
demo_frequency: "biweekly"
state_management: "bloc"
database: "firebase"
auth_method: "jwt"
From Markdown Body:
Extract Features section - look for:
## Features & User Stories
### Epic 1: User Authentication
Priority: P0
Complexity: Medium
**User Stories:**
- As a user, I want to log in securely
- As a user, I want biometric authentication
**Acceptance Criteria:**
- JWT verification (RS256)
- MFA support
- Session timeout (15 min)
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.
- 4d ago First seen · 864 lines · 17 tokens per session scan A 41c360edf55f
Generate Implementation Plan is a command published in the GitHub repository Kandil7/prprompts-flutter-generator (11 stars, last pushed 9mo ago), licensed MIT. It adds 17 tokens to every session and 6,958 once invoked, about $0.0001 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 commands, from other repositories
speckit.gh-triage.triage
Fetch open GitHub issues, classify each as bug, feature, or chore, then DELEGATE to the correct extension: bugs → bug.fetch (saved under .specify/bugs/), chores → chore.fetch (saved under .specify/chores/), features → speckit.specify (saved under specs/). Never save bugs or chores as specs.
speckit.chore.fetch
Load an existing GitHub issue into the chore workflow and seed a triage draft.
speckit.chore.implement
Implement the scoped chore (the actual maintenance work) and record what changed.
speckit.bug.issue
File a GitHub issue from a bug assessment (the 'report' phase) and record the issue link.
speckit.chore.issue
File a GitHub issue from a chore assessment (the 'report' phase) and record the issue link.
speckit.gh-triage.feature
Create a GitHub issue describing a new feature, label it with the configured feature label, and optionally auto-run speckit.specify to turn it into a spec.