dsh-TUI is a terminal interface plugin for DeepSeek Harness that gives the coding agent a Claude Code-style display with live status, streaming thoughts, rollback, context usage, and TPS information. It is for users who prefer a richer terminal workflow, and the catalogue entries extend the DeepSeek Harness environment with related skills and instructions.
Borrowing it
Nothing to install: this file belongs to ccch1mneyyy/dsh-TUI. 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/ccch1mneyyy/dsh-TUI/main/.agents/skills/review/SKILL.mdgit clone --depth 1 https://github.com/ccch1mneyyy/dsh-TUIWrote 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/ccch1mneyyy/dsh-tui/review)<a href="https://agentmods.dev/skills/ccch1mneyyy/dsh-tui/review"><img src="https://agentmods.dev/badge/skills/ccch1mneyyy/dsh-tui/review/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/ccch1mneyyy/dsh-tui/review"><img src="https://agentmods.dev/badge/skills/ccch1mneyyy/dsh-tui/review.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 | $0.00039 | $0.00291 |
| Opus 5 | $0.00019 | $0.00146 |
| Sonnet 5 | $0.00008 | $0.00058 |
| Haiku 4.5 | $0.00004 | $0.00029 |
Grade A, and why
review 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 yesterday.
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.
What it actually says
Review the requested scope and report actionable findings. If the user also asked for fixes, implement and verify them after establishing the cause.
- Identify the target and actual base. For a stacked PR, compare with its parent branch; for a local change, include the requested staged or unstaged work. Read changed code with its callers and relevant tests.
- Trace behavior across the affected boundaries: DSH event projection, channel actions, input precedence, or terminal lifecycle. Check failure paths and resource cleanup, and whether tests cover the changed behavior rather than mirror the implementation. Before calling code dead or an abstraction unnecessary, check exports, dynamic registration, compatibility requirements, and other consumers.
- Verify each suspected issue against the implementation and existing guards. Report its location, concrete trigger, impact, and smallest useful fix, ordered by severity. Separate demonstrated defects from optional simplifications.
- Use a short call tree or before/after diff when it explains an ownership or ordering problem more clearly than prose. Show only the affected path and use real symbols from the code.
- State what was reviewed and any verification limits. If there are no actionable findings, say so; do not manufacture nits or add a compulsory praise section.
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.
- yesterday Changed · -13 lines · +2 tokens per session d43d081262a9
- 10d ago First seen · 26 lines · 37 tokens per session scan A 2f41a2b40ca5
review is a skill published in the GitHub repository ccch1mneyyy/dsh-TUI (2,905 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 291 once invoked, about $0.0002 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
review-changes
Review local code changes for concrete correctness, regression, security, and test gaps before shipping.
dsh-code-review
Use when reviewing a pull request in the deepseek-harness repo — orients the reviewer to this codebase's standards (AGENTS.md conventions, defensive patterns, ADRs, quality gates) and the review-specific checks that code alone can't show.
dsh-find-simplifications
Use when working in the deepseek-harness repo to find non-obvious simplification candidates, remove redundant comments or implementation-heavy documentation, write proposed Agent Notes or inline TODO/FIXME/XXX notes, audit or coalesce superseded Agent Notes, or fold worthwhile simplification ideas from another PR…
submit-dsh-plugin
A submission checklist and workflow for adding a DeepSeek Harness plugin to the community’s public catalogue. It prepares the catalogue entry and checks the plugin’s repository, metadata, tests, and required files.
karpathy-guidelines
A set of coding guidelines based on observations about common mistakes made by language models. It emphasizes simple solutions, small targeted edits, clear assumptions, and checkable results.
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…