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 skills/firstp1ck/pi-coding-agent-forge/tech-deep-divenpx skills add Firstp1ck/pi-coding-agent-forge --skill tech-deep-divegit clone --depth 1 https://github.com/Firstp1ck/pi-coding-agent-forgeWhat 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 | $0.00047 | $0.01131 |
| Opus 5 | $0.00023 | $0.00566 |
| Sonnet 5 | $0.00009 | $0.00226 |
| Haiku 4.5 | $0.00005 | $0.00113 |
Grade A, and why
tech-deep-dive 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technology Deep Dive
Evaluate and compare technologies for specific use cases.
If the requesting agent provides a fixed output contract, keep this evaluation process but deliver the final result in the requested structure instead of the default markdown sections below.
Depth and sources per candidate
| Depth | When to use | Minimum distinct sources per candidate |
|---|---|---|
| Standard | Typical pick-one or compare-a-few decision | ≥ 3 (e.g. official docs + registry + one independent benchmark or reputable article) |
| Deep | High impact, contentious options, or regulatory/security-sensitive choice | ≥ 8 across docs, issues, benchmarks, adoption signals, and primary references |
If sources fall short, say so explicitly under each candidate and in the recommendation — do not pad with duplicate pages from the same site.
Parallel evaluation
- After Step 2, plan one stream per candidate (or per evaluation axis if fewer round-trips: e.g. all “license + maintenance” queries in one batch, then all “performance” queries).
- Run streams in parallel when the runtime allows: batch
web_search/web_fetchper candidate rather than finishing A completely before starting B. - Merge only in Step 4 — scoring tables and narrative per candidate should be complete before the side-by-side comparison; resolve contradictions during merge.
- Optional: delegate worker-sized shards (one candidate, fixed headings) via subagents when OpenClaw supports it; the lead turn owns Step 4–5.
Evaluation Criteria
Score each technology on these dimensions (1-5 scale):
| Criterion | What to Assess |
|---|---|
| Fitness for purpose | Does it solve the actual problem? How well? |
| Maturity | Stable releases, battle-tested, production users |
| Ecosystem | Documentation, community, plugins/extensions, examples |
| Maintenance health | Recent commits, release cadence, maintainer count |
| Performance | Benchmarks, known performance characteristics |
| API quality | Ergonomics, type safety, error handling, learning curve |
| Integration | Compatibility with current stack (Rust, TS, Python) |
| License | OSS license compatibility, commercial restrictions |
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 · 119 lines · 47 tokens per session scan A 4c74f69be184
tech-deep-dive is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (74 stars, last pushed 3d ago), licensed MIT. It adds 47 tokens to every session and 1,131 once invoked, about $0.0002 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 skills, from other repositories
github-release-management
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management.
flow-nexus-platform
Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges.
github-code-review
Comprehensive GitHub code review with AI-powered swarm coordination.
github-multi-repo
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration.
github-project-management
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning.
github-workflow-automation
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management.