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 skills add Firstp1ck/pi-coding-agent-forge --skill writer-readergit clone --depth 1 https://github.com/Firstp1ck/pi-coding-agent-forgeWrote 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/firstp1ck/pi-coding-agent-forge/writer-reader)<a href="https://agentmods.dev/skills/firstp1ck/pi-coding-agent-forge/writer-reader"><img src="https://agentmods.dev/badge/skills/firstp1ck/pi-coding-agent-forge/writer-reader/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/firstp1ck/pi-coding-agent-forge/writer-reader"><img src="https://agentmods.dev/badge/skills/firstp1ck/pi-coding-agent-forge/writer-reader.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 | $0.00034 | $0.00336 |
| Opus 5.5 | $0.00014 | $0.00134 |
| Sonnet 5.5 | $0.00007 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
writer-reader 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 28d 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.
What it actually says
Reader response
When to use
Use when the author wants to know where a scene loses attention, reveals too much, confuses a newcomer, or fails to deliver an intended emotion.
Inputs and assumptions
Specify the reader's familiarity, preferences, and available prior chapters. Do not give a first-time reader access to the outline or secret canon.
Portable workflow
- Read the passage in order using only information the specified reader would possess.
- Record reactions at meaningful turns: what is expected, questioned, feared, understood, or misread.
- Separate immediate reaction from later craft diagnosis.
- Identify which questions create productive curiosity and which prevent basic comprehension.
- Compare the experience with the author's intended effect without treating preference differences as errors.
- Return a small set of passage-linked observations and possible experiments for revision.
Safety and side effects
Read-only by default. A model-generated reader persona is not a real beta reader or market sample. Do not claim universal audience response.
Scripts, references, and dependencies
No external dependencies. Use review guidance to distinguish evidence, inference, and taste.
Verification
Check that reactions do not rely on future knowledge and that each major claim points to a passage. State which prior chapters were available.
Pi adapter
Use /writer review --brief "Read as a newcomer who enjoys quiet fantasy; mark confusion separately from suspense".
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.
- 28d ago First seen · 41 lines · 34 tokens per session scan A 1e2624288ca5
writer-reader is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (91 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 336 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-19.
Other skills, from other repositories
convex-component-authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management.
npm-docs
Use this skill whenever the user asks about npm, package management, publishing packages, semantic versioning, npm CLI commands, or Node.js dependencies. Covers npm 12.x including the registry, scopes, organizations, security (audit, provenance, 2FA), CI/CD integration, workspaces, scripts, .npmrc configuration, and…
convex-component-authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management.
dependency-manager
Manage project dependencies — update packages, audit vulnerabilities, resolve conflicts, and keep dependencies healthy. Use when updating packages, fixing vulnerability alerts, or resolving dependency issues.
colab-finetuning
Fine-tune LLMs on Google Colab GPUs directly from openscience. Connects to Colab runtimes via WebSocket bridge for remote training with Unsloth. Supports SFT, GRPO, DPO, vision, and TTS workflows on free T4 to Pro A100 GPUs.
swarm-pr-review
Run a graph-guided, tool-augmented PR review using context packing, parallel exploration, mandatory repository-agnostic risk-family coverage with dispatch scaled to diff size and risk, independent reviewer validation, critic challenge, and metrics writeback. Use for deep pull request review with low false-positive…