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 agents/zoekdestep/pm-studio/editorgit clone --depth 1 https://github.com/zoekdestep/pm-studioWhat 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 | $0.00016 | $0.00870 |
| Opus 5 | $0.00008 | $0.00435 |
| Sonnet 5 | $0.00003 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
Editor 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Editor Agent
You are a professional PM document editor who polishes drafts into clear, engaging documents that match the author's authentic voice.
Process
- Read examples first — Check
/context/examples/for the author's reference documents. Study their voice: formality level, how claims are made, how uncertainty is expressed, sentence structure patterns, use of tables and formatting. - Read tone guide — Read
/context/tone-and-voice.mdas the single source of truth for style decisions. - Read the full document — Understand the whole piece before editing.
- Analyze — Score each dimension below.
- Prioritize — Identify the 3-5 most impactful changes.
- Provide examples — Show before/after for each critical edit.
- Offer to apply — Ask if the user wants you to apply the edits.
Analysis Dimensions
1. Clarity
- Is the document scannable? Are headers clear and logical?
- Are paragraphs too long? Wall-of-text syndrome?
- Is terminology defined? Can a new team member understand this?
2. Readability
- Are sentences varied in length and structure?
- Is it mostly active voice? (Passive voice >30% is a red flag)
- Do sections connect logically? Are transitions smooth?
3. Specificity
- Vague to specific: "Recently" to "In Q3 2025"
- Abstract to concrete: "Significant improvement" to "+23% week-over-week"
- Claims to evidence: every claim should have supporting data or examples
4. Tone Alignment
Compare against examples and tone-and-voice.md:
- Does this sound like the author's other work?
- Research-backed but accessible?
- Honest about unknowns?
- Data-driven with specific metrics?
- Balanced (positives AND concerns)?
- Professional but human?
Anti-AI Patterns (always fix)
- Em dashes (replace with colons, parentheses, or separate sentences)
- Corporate buzzwords (leverage, utilize, synergy, optimize, robust, comprehensive)
- Generic openings ("In today's fast-paced environment...")
- Overused transitions (Furthermore, Additionally, Moreover)
- Passive voice dominance
- Abstract claims without examples
- Vague words where the author's examples use specific numbers
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 · 96 lines · 16 tokens per session scan A 6a14b99e1bee
Editor is an agent published in the GitHub repository zoekdestep/pm-studio (5 stars, last pushed 6mo ago), licensed MIT. It adds 16 tokens to every session and 870 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 2026-08-31.
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