Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/CarbeneAI/Forgenpx agentmods add skills/carbeneai/forge/executingplansWrote 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/skills/carbeneai/forge/executingplans)<a href="https://agentmods.dev/skills/carbeneai/forge/executingplans"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/executingplans/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/skills/carbeneai/forge/executingplans"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/executingplans.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 | $0.00075 | $0.03438 |
| Opus 5.5 | $0.00030 | $0.01375 |
| Sonnet 5.5 | $0.00015 | $0.00688 |
| Haiku 4.5 | $0.00007 | $0.00344 |
Grade A, and why
executing-plans scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
$ curl -X POST http://localhost:3000/api/login \ How it starts
The opening of the file, as written. The whole thing — 670 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executing Plans
Systematically execute written implementation plans with batch processing, verification checkpoints, and progress reporting.
🎯 Load Full CORE Context
read ${PAI_DIR}/skills/CORE/SKILL.md
When to Activate This Skill
- "execute the plan at docs/plans/..." → Systematic implementation
- "implement from the plan" → Follow written specification
- "start working on the plan" → Batch execution with checkpoints
- User has written plan ready to execute
Core Philosophy
Plans Are Single Source of Truth
The plan document specifies:
- What to build
- How to build it
- What order to build it
- How to verify each step
Follow the plan exactly. Don't improvise or "improve" unless explicitly discussed with user.
Batch Execution with Checkpoints
Execute 3 tasks (default), then STOP and report:
- What was implemented
- Verification output
- Current status
Wait for user feedback before continuing. This enables:
- Course correction if something's wrong
- User awareness of progress
- Clear stopping points
- Better debugging
STOP When Blocked
If you encounter ANY uncertainty:
- Missing file referenced in plan
- Unclear instruction
- Dependency issue
- Environment problem
STOP and ASK. Never guess or make assumptions.
The Five-Step Process
Step 1: Load and Review Plan
Before starting any work:
- Read the entire plan from docs/plans/
- Review critically - does it make sense?
- Check prerequisites - are they met?
- Understand execution order - why this sequence?
- Raise concerns before starting
Critical Questions:
- Is the plan clear and executable?
- Are prerequisites met?
- Do file paths exist or need creation?
- Are dependencies installed?
- Is codebase state ready for this plan?
If you find issues with the plan, STOP and report them before starting.
Example Review:
## Plan Review
**Plan:** docs/plans/2026-02-03-user-auth.md
**Checked:**
- [x] Prerequisites met (Express running, Vitest configured, bcrypt installed)
- [x] File paths make sense (src/models/, tests/, src/services/)
- [x] Task sequence logical (test-first, then implement)
- [x] Verification steps clear
**Concerns:**
- None - plan looks executable
**Ready to start:** YES
Proceeding with first batch (Tasks 1-3).
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 · 670 lines · 75 tokens per session scan A 5e61645a12a0
executing-plans is a skill published in the GitHub repository CarbeneAI/Forge (9 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 3,438 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
scanning-containers-with-trivy-in-cicd
This skill covers integrating Aqua Security's Trivy scanner into CI/CD pipelines for comprehensive container image vulnerability detection. It addresses scanning Docker images for OS package and application dependency CVEs, detecting misconfigurations in Dockerfiles, scanning filesystem and git repositories, and…
implementing-code-signing-for-artifacts
This skill covers implementing code signing for build artifacts to ensure integrity and authenticity throughout the software supply chain. It addresses signing binaries, packages, and containers using GPG, Sigstore, and platform-specific signing tools, establishing trust chains, and verifying signatures in deployment…
implementing-semgrep-for-custom-sast-rules
Write custom Semgrep SAST rules in YAML to detect application-specific vulnerabilities, enforce coding standards, and integrate into CI/CD pipelines.
building-vulnerability-dashboard-with-defectdojo
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
panguard
AI agent security platform — audit skills, scan for threats, and run 24/7 protection with 9,700+ detection rules.
detecting-aws-credential-exposure-with-trufflehog
Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.