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 mir-am/skills-agents-ai-coding --skill work-reportgit clone --depth 1 https://github.com/mir-am/skills-agents-ai-codingWrote 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/mir-am/skills-agents-ai-coding/work-report)<a href="https://agentmods.dev/skills/mir-am/skills-agents-ai-coding/work-report"><img src="https://agentmods.dev/badge/skills/mir-am/skills-agents-ai-coding/work-report.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 | $0.00024 | $0.01821 |
| Opus 5 | $0.00012 | $0.00911 |
| Sonnet 5 | $0.00005 | $0.00364 |
| Haiku 4.5 | $0.00002 | $0.00182 |
Grade A, and why
work-report 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 8d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What I do
- Create
.opencode/notes/directory in the project if it doesn't exist - Generate one timestamped markdown report file:
YYYY-MM-DD-HHmm-<description>.md - Explain the user's problem, the proposed solution, and why the change matters
- Add enough project and code context for humans and other AI agents to review the work without digging deeply into the repository
- List changed files visible in git, grouped by created, modified, renamed, and deleted
- Capture a concise step-by-step work log describing what the agent inspected, decided, and changed
- Include per-file patch sections with fenced
diffblocks - Use hybrid patch handling: full patches for small files, truncated patches for large files with a
git diffreference - Record tests or validations that were run, if any
When to use me
Use this skill when:
- User asks for a report of the work completed
- User wants a self-contained handoff artifact for later continuation or review
- Agent finishes meaningful code, docs, or config changes and the result should be documented in one place
Report Workflow
-
Create directory:
mkdir -p .opencode/notes -
Generate filename:
- Extract the main task from conversation context
- Format:
YYYY-MM-DD-HHmm-<brief-description>.md - Example:
2026-04-01-1430-add-work-report.md - Description should be kebab-case, concise, and no more than 4-5 words
- Fallback:
work-report
-
Gather task context:
- Identify the problem the user wanted solved
- Identify the scope of work the agent completed
- Summarize the proposed solution chosen by the agent
- Capture why this change matters to the user or project
-
Gather project context:
- Identify the subsystem, feature area, or workflow touched
- Summarize how the relevant part of the project worked before the change
- Note important constraints, conventions, or related files reviewers should know
- Include only context that helps understand or review the change; avoid dumping unrelated repo background
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.
- 8d ago First seen · 224 lines · 24 tokens per session scan A 29ea202b73aa
work-report is a skill published in the GitHub repository mir-am/skills-agents-ai-coding (2 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 1,821 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 2026-08-31.
Other skills, from other repositories
skill-creator
Create, improve, evaluate, benchmark skills. Use when authoring a new skill, updating an existing one, running evals, or optimizing a skill's description for triggering. Don't use for invoking skills, writing prose, or scaffolding Python projects.
regulatory-analysis
Analyzes documents and processes against FINRA, SEC, Federal Reserve, and CFPB regulatory frameworks. Identifies compliance gaps, classifies findings by severity, and recommends remediation. Use when performing compliance audits, regulatory reviews, gap analyses, or verifying policy adherence to financial regulations.
export-agent
Converts agent definitions between frameworks — exports to Claude Code, OpenAI, CrewAI, Lyzr, and GitHub Models formats, and imports from Claude, Cursor, and CrewAI projects. Use when the user wants to convert an agent, migrate to another framework, export to LangChain/AutoGen/CrewAI, or import from existing…
manage-skills
Searches the SkillsMP registry, installs skills locally or globally, creates custom skills with SKILL.md frontmatter, and manages the skill lifecycle. Use when the user wants to find skills, add new capabilities, install a skill, browse available skills, create a custom skill, or manage the skills system.
run-agent
Configures and runs agents with different adapters including Claude, OpenAI, CrewAI, Lyzr, and GitHub Models. Supports local execution, remote git repos, and one-shot prompts. Use when the user wants to run an agent, switch LLM providers, configure adapter settings, or launch agents from git repositories.
skill-index-updater
Add GitHub skill repos to the ASM index: clone, audit, eval, regenerate index, rebuild catalog, open PR. Use when given GitHub URLs to onboard. Don't use for authoring (skill-creator), improving (skill-auto-improver), or install (asm install).