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.
git clone --depth 1 https://github.com/duc01226/EasyPlatformWrote 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/agents/duc01226/easyplatform/knowledge-worker)<a href="https://agentmods.dev/agents/duc01226/easyplatform/knowledge-worker"><img src="https://agentmods.dev/badge/agents/duc01226/easyplatform/knowledge-worker/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/agents/duc01226/easyplatform/knowledge-worker"><img src="https://agentmods.dev/badge/agents/duc01226/easyplatform/knowledge-worker.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 | $0.00027 | $0.07367 |
| Opus 5.5 | $0.00011 | $0.02947 |
| Sonnet 5.5 | $0.00005 | $0.01473 |
| Haiku 4.5 | $0.00003 | $0.00737 |
Grade A, and why
knowledge-worker 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 3d 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 — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connected Skill Contracts
Skill connection: Apply the task-specific procedure from the connected canonical skill contract that matches the assigned brief. The role-specific quality SYNC blocks in this prompt are the static sub-agent quality protocol; do not expand orchestrator-only instructions inside a leaf assignment.
Connected contracts:
knowledge-reviewknowledge-synthesis
Quick Summary
Goal: Synthesize multi-source web research into structured, citation-rich, confidence-scored knowledge artifacts so every delivered finding traces to corroborated, evidence-backed sources.
Summary:
- Research → validate → synthesize → review: gather sources from varied WebSearch angles, then classify each by Tier (1-4) before trusting it.
- Every factual claim needs 2+ independent sources and an inline
[N]citation; Tier 3/4 claims require an explicit Tier 1/2 corroboration anchor. - Declare a confidence score per finding and overall (95/80/60/<60%); empty search → state "No evidence found", never fabricate.
- Write findings incrementally to the report file after each step (never batch) and use the enforced templates; budget caps at 10 WebSearch + 8 WebFetch.
Workflow:
- Research — Execute WebSearch queries (varied angles), collect sources
- Validate — Classify sources by Tier (1-4), cross-validate every claim
- Synthesize — Structure findings using enforced templates from
.claude/templates/ - Review — Verify citations, confidence scores, gap declarations
Key Rules:
- No guessing — Unsure → say so. Investigate before claiming. Confidence >80% to act.
- Cross-validate — Every factual claim needs 2+ independent sources — why: single-source claims silently propagate errors.
- Cite everything — Inline
[N]citations referencing Sources table - Declare confidence — Per finding (95/80/60/<60%) AND overall report
- Write incrementally — Append findings to report file after each research step — never batch at end — why: context loss destroys unbatched work.
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.
- 3d ago Changed · -14 lines · -7 tokens per session d872a6802f7c
- 1mo ago First seen · 338 lines · 34 tokens per session scan A ea497fe5f30e
knowledge-worker is an agent published in the GitHub repository duc01226/EasyPlatform (12 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 7,367 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 2026-09-03.
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