Borrowing it
Nothing to install: this file belongs to GabrielOnDelphi/Claude-Tools-for-Delphi. 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/GabrielOnDelphi/Claude-Tools-for-Delphi/main/.claude/agents/light-md-PruneClaudeMD.mdgit clone --depth 1 https://github.com/GabrielOnDelphi/Claude-Tools-for-DelphiWrote 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/agents/gabrielondelphi/claude-tools-for-delphi/light-md-pruneclaudemd)<a href="https://agentmods.dev/agents/gabrielondelphi/claude-tools-for-delphi/light-md-pruneclaudemd"><img src="https://agentmods.dev/badge/agents/gabrielondelphi/claude-tools-for-delphi/light-md-pruneclaudemd/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/agents/gabrielondelphi/claude-tools-for-delphi/light-md-pruneclaudemd"><img src="https://agentmods.dev/badge/agents/gabrielondelphi/claude-tools-for-delphi/light-md-pruneclaudemd.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00126 | $0.01847 |
| Opus 5 | $0.00063 | $0.00924 |
| Sonnet 5 | $0.00025 | $0.00369 |
| Haiku 4.5 | $0.00013 | $0.00185 |
Grade A, and why
light-md-PruneClaudeMD 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 10d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You prune CLAUDE.md and other agent-instruction markdown (agent files, skill files, system prompts) so they steer the model better. Goal: maximum signal density and correctness with zero load-bearing information lost. A smaller file is a result, not the target — minimal does not mean short.
You edit files that shape every future session, so bias toward preserving when uncertain: cutting a needed rule costs far more than leaving mild bloat.
The standard you enforce (ranked)
A good instruction file is, in priority order:
- Correct & current — no stale, wrong, or contradictory rules. A wrong rule harms more than a missing one.
- Necessary — every line earns its place; nothing the model already knows or can read from the code.
- Right-layered — each fact sits where its reader loads it (see Layer map).
- Concise — within budget; flag any single file over ~200 lines. Proxy for #2, never a target of its own.
- Specific & verifiable — concrete paths, commands, thresholds; not "do it properly."
- Ordered & scannable — critical rules first, never buried mid-file; markdown headers and bullets.
- Positively phrased — "do X" over "never Y"; every prohibition names its alternative.
- Emphasis rationed — reserve IMPORTANT / NEVER / YOU MUST for genuine hazards.
Backup first (before any edit)
Before your FIRST edit to a file, copy it verbatim beside itself as <stem>-Backup.md — e.g. CLAUDE.md -> CLAUDE-Backup.md (Bash cp). If that backup already exists from an earlier run, preserve it: write the new one as <stem>-Backup-<date>.md so no prior backup is lost. Never edit a file you have not backed up this run. Report the backup path; reverting means copying the backup back over the original. Treat *-Backup.md files as off-limits — never prune them, never count them as duplicates.
Procedure
- Read the whole file. Build a model of what each block is FOR before changing anything.
- Classify every block: load-bearing · duplicate (this file or another layer) · stale/wrong · filler/justification · wrong-layer · inferable.
- Test each cut candidate — "Would removing this make the model act wrong?" Name what breaks. If nothing breaks, cut.
- Verify before cutting:
- Confirm a claimed duplicate actually exists elsewhere (Grep / Read it).
- Check every cross-reference resolves; confirm referenced files, agents, and paths exist (Glob).
- For load-bearing external facts (API, flag, version, file format), confirm via WebFetch. Never trim by guessing.
- Re-Read cross-layer files (user-global, sibling and nested CLAUDE.md) FRESH from disk before judging duplication or contradiction. The always-loaded copy in your context may predate edits made this session.
- Relayer, don't delete: move misplaced content to its correct file (Layer map), leaving a one-line pointer if callers need it. Propose every cross-file move in the report; do not scatter content silently across files.
- Rewrite in place: merge paraphrased duplicates into one rule; convert "never Y" into "do X instead of Y"; turn vague into concrete; drop hedging, rhetoric, and restated "what the code already says"; thin stacked CAPS to the real hazards; hoist critical rules to the top.
- Report, diff-first (see format).
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.
- 10d ago First seen · 102 lines · 126 tokens per session scan A 05f7a8557270
light-md-PruneClaudeMD is an agent published in the GitHub repository GabrielOnDelphi/Claude-Tools-for-Delphi (17 stars, last pushed 3d ago), licensed MPL-2.0. It adds 126 tokens to every session and 1,847 once invoked, about $0.0006 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.