Softaworks Agent Toolkit is a collection of packaged instructions, scripts, agents, and commands that give AI coding assistants reusable procedures for development, documentation, planning, and professional work. Developers install its components individually in compatible coding-agent environments; catalogue entries represent parts of this toolkit.
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 softaworks/agent-toolkit --skill daily-meeting-updategit clone --depth 1 https://github.com/softaworks/agent-toolkitWrote 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/softaworks/agent-toolkit/daily-meeting-update)<a href="https://agentmods.dev/skills/softaworks/agent-toolkit/daily-meeting-update"><img src="https://agentmods.dev/badge/skills/softaworks/agent-toolkit/daily-meeting-update/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/softaworks/agent-toolkit/daily-meeting-update"><img src="https://agentmods.dev/badge/skills/softaworks/agent-toolkit/daily-meeting-update.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 393 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00094 | $0.02888 |
| Opus 5 | $0.00047 | $0.01444 |
| Sonnet 5 | $0.00019 | $0.00578 |
| Haiku 4.5 | $0.00009 | $0.00289 |
Grade A, and why
daily-meeting-update 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.
How it starts
The opening of the file, as written. The whole thing — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Meeting Update
Generate a daily standup/meeting update through an interactive interview. Never assume tools are configured—ask first.
Workflow
START
│
▼
┌─────────────────────────────────────────────────────┐
│ Phase 1: DETECT & OFFER INTEGRATIONS │
│ • Check: Claude Code history? gh CLI? jira CLI? │
│ • Claude Code → Pull yesterday's session digest │
│ → User selects relevant items via multiSelect │
│ • GitHub/Jira → Ask user, pull if approved │
│ • Pull data NOW (before interview) │
├─────────────────────────────────────────────────────┤
│ Phase 2: INTERVIEW (with insights) │
│ • Show pulled data as context │
│ • Yesterday: "I see you merged PR #123, what else?" │
│ • Today: What will you work on? │
│ • Blockers: Anything blocking you? │
│ • Topics: Anything to discuss at end of meeting? │
├─────────────────────────────────────────────────────┤
│ Phase 3: GENERATE UPDATE │
│ • Combine interview answers + tool data │
│ • Format as clean Markdown │
│ • Present to user │
└─────────────────────────────────────────────────────┘
Phase 1: Detect & Offer Integrations
Step 1: Silent Detection
Check for available integrations silently (suppress errors, don't show to user):
| Integration | Detection |
|---|---|
| Claude Code History | ~/.claude/projects directory exists with .jsonl files |
| GitHub CLI | gh auth status succeeds |
| Jira CLI | jira command exists |
| Atlassian MCP | mcp__atlassian__* tools available |
| Git | Inside a git repository |
Step 2: Offer GitHub/Jira Integrations (if available)
Claude Code users: Use
AskUserQuestionTooltool for all questions in this phase.
GitHub/Git:
If HAS_GH or HAS_GIT:
"I detected you have GitHub/Git configured. Want me to pull your recent activity (commits, PRs, reviews)?"
Options:
- "Yes, pull the info"
- "No, I'll provide everything manually"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 409 lines · 94 tokens per session scan A 153c2d8ddee3
daily-meeting-update is a skill published in the GitHub repository softaworks/agent-toolkit (2,446 stars, last pushed 6mo ago), licensed MIT. It adds 94 tokens to every session and 2,888 once invoked, about $0.0005 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
process-doc
Turn an operational process into a clear SOP, role model, control map, and improvement backlog.
implement-issue
Take a GitHub issue from planning to PR, resumable across clarification waits.
ce:work
Execute work plans efficiently while maintaining quality and finishing features.
control-plane-ops
Operar o control-plane local-first do agents-lab com board canônico, long-runs bounded, handoff/checkpoint, rollout/rollback e espelhos externos sem perder governança.
review-health
Audit any repository's structural health and file the findings as proposed epics and one-PR issues.
plan-backlog
Turn a vision document into a curated backlog of proposed epics and one-PR issues.