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/competitor-analysisnpx skills add Firstp1ck/pi-coding-agent-forge --skill competitor-analysisgit 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 | $0.00043 | $0.00889 |
| Opus 5 | $0.00022 | $0.00445 |
| Sonnet 5 | $0.00009 | $0.00178 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
competitor-analysis 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Analysis
Research competitive landscape and produce actionable comparisons.
Product stream vs market stream
Split investigation to mirror parallel research patterns; merge before strategic recommendations.
| Stream | Focus | Typical sources |
|---|---|---|
| Product | Feature matrix, specs, APIs, pricing tables, integrations, release cadence | Official docs, changelogs, pricing pages, registries |
| Market | Positioning, messaging, ICP, reviews, sentiment, analyst takes, share/narrative | G2/Capterra, HN/Reddit, landing copy, news, reports |
Execution: Run both streams in parallel (batched searches/fetches per stream) when possible. If using subagents, assign one stream per worker with a fixed handoff schema (bullets + URLs); one synthesis pass produces Steps 3–6 below.
Process
Step 1 — Define Scope
**Subject:** [What product/feature we're analyzing]
**Competitors to evaluate:** [Specific names, or "discover competitors"]
**Purpose:** [What decision this informs]
**Dimensions:** [Features, pricing, UX, performance, target audience]
Step 2 — Discover Competitors
Assign discovery to both streams: product-side (direct substitutes, OSS alternatives) and market-side (who buyers compare you to in reviews and “vs” articles).
If competitors aren't specified:
- Search for "[category] alternatives"
- Check comparison sites (G2, AlternativeTo, Product Hunt)
- Search GitHub for open-source alternatives
- Check Hacker News and Reddit for community recommendations
- Review industry reports and analyst coverage
Step 3 — Feature Matrix (product stream)
## Feature Comparison
| Feature | Our Product | Competitor A | Competitor B | Competitor C |
|---|---|---|---|---|
| [Feature 1] | Yes | Yes | No | Partial |
| [Feature 2] | Planned | Yes | Yes | Yes |
| [Feature 3] | No | No | Yes | No |
| **Pricing** | [model] | [model] | [model] | [model] |
| **Target audience** | [who] | [who] | [who] | [who] |
| **Open source** | Yes/No | Yes/No | Yes/No | Yes/No |
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 · 118 lines · 43 tokens per session scan A 8b90ecee6423
competitor-analysis is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (74 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 889 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.
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