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 kensaurus/cursor-kenji --skill burndown-fullgit clone --depth 1 https://github.com/kensaurus/cursor-kenjiWrote 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/kensaurus/cursor-kenji/burndown-full)<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/burndown-full"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/burndown-full/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/kensaurus/cursor-kenji/burndown-full"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/burndown-full.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 | $0.00059 | $0.02933 |
| Opus 5.5 | $0.00024 | $0.01173 |
| Sonnet 5.5 | $0.00012 | $0.00587 |
| Haiku 4.5 | $0.00006 | $0.00293 |
Grade A, and why
burndown-full 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 26d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Burndown Full
Degree of freedom: MIXED. Signature and batch sizing [HIGH freedom];
from-scratch re-search and the zero-hit gate [LOW freedom — run exactly].
How to reason
- Observe — the old pattern's remaining hits from a fresh search
- Interpret — planned files vs the real blast radius (tests, barrels, stories)
- Classify — still-old / already-new / false-positive
- Severity — leftover production call sites outrank a comment in CHANGELOG
Worked example
Observe: plan listed 8 files; fresh
rg Button2finds 14 (plus a story and a re-export). Interpret: the plan was a hypothesis; barrels were missed. Classify: 6 extra call sites still-old; CHANGELOG mention is false-positive. Done: re-search → 0 real hits; typecheck/lint/tests green.
Self-critique before reporting
- Fresh search — done is zero hits from scratch, not memory
- Plan is not the boundary — extras were appended, not ignored
- No skip — tests/stories/re-exports burned down too
- Right owner — one approved plan + deferrals →
complete-everything; inventory →housekeep-backlog
What problem this solves
A coding agent is given a plan, generates it, starts executing, and then stops before the change is actually complete across the codebase. The user is left with a half-migrated repo. This is not a motivation problem — it is a well-documented set of failure modes in long-horizon LLM agents:
- Compaction. Long runs get compacted; anything that lived only in the transcript — including "what's left to do" — is gone afterwards. The remaining work has to live in a file.
- Premature termination. When tool outputs and history get pruned or summarized to save context, agents lose task-level awareness ("how many items remain, am I near done?") and declare completion early. The fix shown in the research is to keep a condensed, persistent record of remaining work visible at all times.
- Plan-as-boundary error. A plan is a hypothesis about scope produced before the repo was fully explored. The real set of affected files is almost always larger than the plan's list (barrels, tests, stories, configs, re-exports, dynamic usages). Treating the plan's file list as the boundary guarantees an incomplete burndown.
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.
- 26d ago Changed f089e395ff8c
- 1mo ago Changed · -1 lines · -11 tokens per session 7de2919182fe
- 1mo ago First seen · 176 lines · 70 tokens per session scan A 106bc038cb79
burndown-full is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 27d ago), licensed MIT. It adds 59 tokens to every session and 2,933 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.
Other skills, from other repositories
commit
Generate a conventional commit message for staged changes.
git-sync-workspace
Sync every git repo in a Cursor multi-root workspace to its remote default branch: discover roots, preflight each repo, fetch --all --prune, checkout default, pull --ff-only. Skips dirty or unsafe repos with a clear report. Use for "sync workspace", "update all repos", "back to main", or reset workspace repos to…
commit-changes-main
Commit directly on main/master when explicitly allowed.
address-github-pr-comments
Address review comments on the current GitHub PR.
generate-pr-description
Generate PR title and description from branch diff.
fix-issue
Fix a GitHub issue end-to-end. Use when given an issue number to fix, implementing bug fixes, or addressing reported problems.