Knowledge Work Plugins is an open-source collection of Claude extensions organized around roles such as productivity, sales, and customer support. Each plugin combines role-specific guidance, connectors, commands, and sub-agents so knowledge workers can use Claude with their team’s tools and processes. The catalogue entries are examples of, or workflows from, this plugin collection.
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/anthropics/knowledge-work-pluginsWrote 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/commands/anthropics/knowledge-work-plugins/channel-digest)<a href="https://agentmods.dev/commands/anthropics/knowledge-work-plugins/channel-digest"><img src="https://agentmods.dev/badge/commands/anthropics/knowledge-work-plugins/channel-digest.svg" alt="Measured on agentmods" 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 | $0.00010 | $0.00276 |
| Opus 5 | $0.00005 | $0.00138 |
| Sonnet 5 | $0.00002 | $0.00055 |
| Haiku 4.5 | $0.00001 | $0.00028 |
Grade A, and why
channel-digest 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 4d 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
1 near-identical copy found in the catalogue:
- channel-digest — 100% identical, 8 lines differ
What it actually says
Given the comma-separated channel names provided in $ARGUMENTS (strip leading # and whitespace from each):
-
Parse the argument into individual channel names. Strip leading
#and whitespace from each name. -
For each channel: a. Use
slack_search_channelsto find the channel ID. b. Useslack_read_channelto read recent messages (use a limit of 50 messages per channel to keep things manageable). c. Summarize the key activity in that channel: main topics, decisions, questions, and notable messages. -
Present the digest in this format:
*Channel Digest — <today's date>* *#channel-1* - Summary point 1 - Summary point 2 *#channel-2* - Summary point 1 - Summary point 2 ... -
For each channel, keep the summary to 3-5 bullet points maximum. Focus on what's actionable or noteworthy.
-
If a channel has no recent activity, note that it's been quiet and mention when the last message was posted (if visible).
-
If a channel name can't be found, let the user know and continue with the remaining channels.
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.
- 4d ago First seen · 35 lines · 10 tokens per session scan A 4445bdab0422
channel-digest is a command published in the GitHub repository anthropics/knowledge-work-plugins (23,911 stars, last pushed 2d ago), licensed Apache-2.0. It adds 10 tokens to every session and 276 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 2026-09-03.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.