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 stevesolun/ctx --skill writing-fragmentsgit clone --depth 1 https://github.com/stevesolun/ctxWrote 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/stevesolun/ctx/writing-fragments)<a href="https://agentmods.dev/skills/stevesolun/ctx/writing-fragments"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/writing-fragments/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/stevesolun/ctx/writing-fragments"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/writing-fragments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.00723 |
| Opus 5 | $0.00040 | $0.00362 |
| Sonnet 5 | $0.00016 | $0.00145 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
writing-fragments 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 9d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- writing-fragments — 100% identical, 0 lines differ
- writing-fragments — 100% identical, 0 lines differ
- writing-fragments — 100% identical, 0 lines differ
- writing-fragments — 100% identical, 0 lines differ
- writing-fragments — 100% identical, 0 lines differ
- ideation-fragment-collector — 97% identical, 2 lines differ
- writing-fragments — 95% identical, 5 lines differ
- writing-fragments — 94% identical, 16 lines differ
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a grilling session that produces fragments. Interview the user relentlessly about whatever they want to write about. Do not impose phases, outlines, or structure — that is explicitly out of scope.
As fragments emerge from either side of the conversation, append them to a single markdown file. The user will be editing this file during the session; always re-read it before writing so their edits are preserved.
If the user did not pass a path, ask once where to save the document, then remember it for the rest of the session.
Capture fragments from the very first thing the user says, including the initial prompt.
On first write, put a single H1 at the top with a working title (it can change later) and nothing else — no metadata, no TOC, no date.
What is a fragment
A fragment is any piece of text that might survive into the final article. It must be readable by the author — the author can tell what it means — but it does not need to define its terms or be comprehensible to a cold reader. The bar is "is this a piece of good writing?", not "is this a self-contained argument?"
Fragments are deliberately heterogeneous. Examples of what could be a fragment:
- A sharp sentence you'd want to deploy somewhere but don't yet know where.
- A claim with a one-line justification.
- A vignette: a thing that happened, a code snippet, a scenario, an analogy.
- A half-thought: "something about how X feels like Y, work this out later."
- A quote, a piece of dialogue, an overheard line.
- A list of related observations that hang together by feel.
- A complaint, a confession, a punchline.
The novelist's diary is the model: years of unstructured noticings that later get mined for raw material. Fragments are noticings.
File format
# Working title
A first fragment lives here.
It can be multiple paragraphs. It can include lists, code, quotes — whatever
shape the fragment naturally takes.
---
A second fragment.
---
> A quoted line that the user wants to keep around.
A reaction to it.
---
- A cluster of related observations
- That hang together by feel
- And want to be near each other
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.
- 9d ago First seen · 76 lines · 80 tokens per session scan A 4ffa34a701ca
writing-fragments is a skill published in the GitHub repository stevesolun/ctx (584 stars, last pushed 9d ago), licensed MIT. It adds 80 tokens to every session and 723 once invoked, about $0.0004 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
security-compliance
Guides security professionals in implementing defense-in-depth security architectures, achieving compliance with industry frameworks (SOC2, ISO27001, GDPR, HIPAA), conducting threat modeling and risk assessments, managing security operations and incident response, and embedding security throughout the SDLC.
stride-analysis-patterns
Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
prompts-chat
Use when searching, installing, or improving AI skills and prompts via prompts.chat or skills.sh. Triggers on skill search, prompt lookup, install skill, improve prompt, prompts.chat.
continuous-learning-v2
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
cc-dev-agent
Use when starting Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev workflow.