Borrowing it
Nothing to install: this file belongs to davidmatousek/tachi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/davidmatousek/tachi/main/.claude/skills/~aod-build/SKILL.mdgit clone --depth 1 https://github.com/davidmatousek/tachiWrote 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/davidmatousek/tachi/aod-build)<a href="https://agentmods.dev/skills/davidmatousek/tachi/aod-build"><img src="https://agentmods.dev/badge/skills/davidmatousek/tachi/aod-build/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/davidmatousek/tachi/aod-build"><img src="https://agentmods.dev/badge/skills/davidmatousek/tachi/aod-build.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.02510 |
| Opus 5.5 | $0.00022 | $0.01004 |
| Sonnet 5.5 | $0.00011 | $0.00502 |
| Haiku 4.5 | $0.00006 | $0.00251 |
Grade A, and why
~aod-build 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 1mo 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:
- ~aod-build — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Checkpoint Skill
Purpose
Automatically generate standardized checkpoint reports that document implementation progress at strategic milestones. Each report includes completed tasks, remaining work, technical achievements, knowledge base entries, quality metrics, and resume instructions.
When to Use
Create a checkpoint at:
- Complete phase finish - All tasks in a phase marked complete
- User story completion - Entire user story implemented and tested
- Critical milestone - Core functionality ready (e.g., MVP core)
- Before pausing - Stopping for review, testing, or user feedback
- After architect review - Major approval/sign-off received
How to Use
Quick Usage
# Navigate to skill directory
cd .claude/skills/~aod-build
# Generate checkpoint (interactive prompts will follow)
python scripts/generate_checkpoint.py \
--tasks-file ../../specs/{feature-id}/tasks.md \
--output-dir ../../specs/{feature-id} \
--description "{Phase-Description}"
Step-by-Step Process
-
Analyze completion status
# Script automatically: # - Reads tasks.md # - Counts [X] completed vs [ ] pending # - Calculates progress percentage # - Identifies completed phases # - Determines task range -
Provide context when prompted
Key achievements (3-5 bullet points): > - Achievement 1 > - Achievement 2 > - Achievement 3 Knowledge base entries captured (count or 'none'): > 2 [For each KB entry, provide: Title, Problem, Solution] -
Review generated report
# Output: CHECKPOINT-{NN}_{Description}_{TaskRange}.md # Location: specs/{feature-id}/ -
Verify index updated
# Check: CHECKPOINTS_README.md includes new checkpoint
Checkpoint Naming Convention
Format: CHECKPOINT-{NN}_{Phase-Description}_{TaskRange}.md
Components:
{NN}: Sequential checkpoint number (01, 02, 03...) - auto-detected{Phase-Description}: Milestone name (e.g., "Phase1-2-Complete", "US1-Complete"){TaskRange}: Task IDs covered (e.g., "T001-T030")
What ships with it
9 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.
- assets/CHECKPOINTS_README_template.md 3.4 KB
- README.md 8.8 KB
- references/checkpoint_template.md 1.7 KB
- references/metrics_formulas.md 6.7 KB
- references/naming_conventions.md 4.5 KB
- scripts/analyze_tasks.py 5.0 KB runs code
- scripts/generate_checkpoint.py 11 KB runs code
- scripts/update_index.py 7.3 KB runs code
- USAGE.md 8.9 KB
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.
- 1mo ago First seen · 338 lines · 56 tokens per session scan A 610e720fee5e
~aod-build is a skill published in the GitHub repository davidmatousek/tachi (94 stars, last pushed 4d ago), licensed Apache-2.0. It adds 56 tokens to every session and 2,510 once invoked, about $0.0002 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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