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 imMamdouhaboammar/get-fable --skill web-researchgit clone --depth 1 https://github.com/imMamdouhaboammar/get-fableWrote 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/immamdouhaboammar/get-fable/web-research)<a href="https://agentmods.dev/skills/immamdouhaboammar/get-fable/web-research"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/web-research/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/immamdouhaboammar/get-fable/web-research"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/web-research.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 | $0.00018 | $0.00448 |
| Opus 5 | $0.00009 | $0.00224 |
| Sonnet 5 | $0.00004 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
web-research 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 6d 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.
This is a copy
88% identical to web-research — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Web research
The user wants findings grounded in current, real sources — not your prior knowledge alone. Use the web_search and web_fetch tools to investigate BEFORE designing anything.
Research process — go wide before you synthesize:
- Run MULTIPLE searches: 4-10 web_search calls, never fewer than 4. One search is not research — it bets everything on your first phrasing. Stop only when new queries stop surfacing new information, even if that takes more than 10.
- Vary the queries: split the ask into concrete sub-questions (specific beats broad) and hit the important ones from several angles — different terms, different source types.
- Pull a LOT of data: web_fetch many results, not just a top hit. Favor the primary sources behind the hits (the paper, the filing, the announcement, the docs — not a blog's summary of them) and extract specifics: numbers, dates, names, direct quotes.
- Cross-check every load-bearing figure across independent sources. When sources disagree, report the disagreement — don't average it away or pick silently.
- Keep the trail: note which source said what as you go, with URLs.
Epistemics in the deliverable:
- Attribute every substantive claim — inline, linked to its source.
- Date what you cite ("as of the 2024 filing…"); stale numbers presented as current are worse than no numbers.
- Separate what sources establish from what you infer, and say which is which. If the evidence is thin or conflicting, the report says so — a confident-sounding gap is the one failure mode to avoid.
Deliverable (unless the user asks for another format): a designed, single-file HTML research report — headline takeaways up top, then findings with their evidence, and a linked source list at the end. Design it like an editorial broadsheet: strong typographic hierarchy, pull quotes for key numbers, charts only where the data earns them.
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.
- 6d ago First seen · 42 lines · 18 tokens per session scan A 33fd40052254
web-research is a skill published in the GitHub repository imMamdouhaboammar/get-fable (4 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 448 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to web-research, differing in 3 lines, and is treated as a copy.
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todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
spec-graph
The project's specs are its ground truth: durable documents describing the architecture, decisions, contracts, and boundaries behind the code, organized as a connected graph. Read this skill and reach for the spec tools FIRST — before reading code — whenever you explore the project, plan or start a task, add or change…
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.