tl-dps-mcp copilot-instructions.md

tl-dps-mcp copilot-instructions.md is an instructions file for GitHub Copilot from stalcup-dev/tl-dps-mcp. It costs 973 tokens per session, scanned A, original, MIT.

A set of coding instructions for a tool that reads Throne & Liberty combat logs and calculates damage-per-second summaries for command-line tools, MCP tools, and a desktop app.

In plain words
What is it for?
Use it when adding or modifying log parsing, damage calculations, reports, MCP responses, or the PySide6 desktop interface.
Why use it?
It keeps the log format, data fields, filtering rules, and rounding consistent across the project, reducing errors when code is changed.

Instructions file for GitHub Copilot

Install

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.

agentmods
npx agentmods add instructions/stalcup-dev/tl-dps-mcp/copilot-instructions
Clone the repo
git clone --depth 1 https://github.com/stalcup-dev/tl-dps-mcp

Made for: GitHub Copilot.

Wrote 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.

agentmods badge for tl-dps-mcp copilot-instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/stalcup-dev/tl-dps-mcp/copilot-instructions.svg)](https://agentmods.dev/instructions/stalcup-dev/tl-dps-mcp/copilot-instructions)
Your own site
<a href="https://agentmods.dev/instructions/stalcup-dev/tl-dps-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/stalcup-dev/tl-dps-mcp/copilot-instructions.svg" alt="Measured on agentmods" height="20"></a>
Per session 973 This file is loaded in full into every session.
When invoked 973 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00973 $0.00973
Opus 5 $0.00487 $0.00487
Sonnet 5 $0.00195 $0.00195
Haiku 4.5 $0.00097 $0.00097

Measured 3d ago against content hash 6ceb33e04bbf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tl-dps-mcp copilot-instructions.md 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 3d 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.

.github/copilot-instructions.md · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TL DPS MCP Copilot Guide

  • Project Intent: Parse Throne & Liberty combat logs into deterministic DPS/DPM summaries consumable by CLI, MCP tools, and the PySide6 desktop app.
  • Data Contract: server.analyze_logs returns the canonical payload (generated_at, source, runs, summary) expected by the CLI, FastMCP tool, markdown reporter, and UI tables—keep field names/types stable.
  • Log Expectations: Parser assumes UTF-8 .txt/.log rows shaped as timestamp,event_type,skill,internal_id,damage,crit_flag,heavy_flag,hit_type,source,target; unexpected column counts are skipped, not fatal.
  • Run Filtering: Only DamageDone rows with damage > 0 contribute to DPS math; maintain _safe_duration fallback to 1.0 seconds to avoid divide-by-zero regressions.
  • Rounding: Metrics are rounded to three decimals (dps, dpm, % helpers) to match validation scripts and sample reports.

Analyzer Stack

  • Parser (dps_logs/parser.py): load_runs yields (run_id, events) covering single files or newest limit_runs in a directory; reuse its iterator instead of reimplementing file discovery.
  • Metrics (dps_logs/metrics.py): summarize_run shapes per-run dictionaries; build_summary merges runs and mirrors top_skills into top_skills_by_damage for downstream consumers—extend both when adding new stats.
  • Reporting (dps_logs/reporting.py): Markdown builder expects the same payload shape and recomputes means/medians; update helper tables when payload fields change.
  • CLI (server.py): Treat analyze_logs as pure; CLI glue handles argparse, pretty-printing, and optional file mirrors via _write_text.
  • MCP (mcp_server.py): FastMCP exposes analyze_dps_logs with identical argument semantics (log_dir, limit_runs); validation relies on parity with analyze_logs.

Desktop App

  • Client (app/mcp_client.py): MCPAnalyzerClient shells out to python -m mcp_server; keep stdout JSON-compatible so _extract_payload can parse either structured or text responses.
  • UI (app/main.py): AnalysisWorker runs analysis on a QThread; update _update_summary, _update_runs_table, _update_skills_table in lockstep with payload changes to avoid KeyErrors.
  • Constants (app/constants.py): Shared defaults live here (log dir autodetect, run limits, banner path, Python executable); adjust limits once so both UI and analyzers stay aligned.
  • Dependencies: Install UI deps via pip install -r app/requirements_app.txt (PySide6 + mcp[cli]); runtime Python 3.11+.

Read the full file on GitHub · 34 lines

Changes

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.

  1. 3d ago First seen · 34 lines · 973 tokens per session scan A 6ceb33e04bbf

Subscribe to this mod's changes

tl-dps-mcp copilot-instructions.md is an instructions file published in the GitHub repository stalcup-dev/tl-dps-mcp (0 stars, last pushed 8mo ago), licensed MIT. It adds 973 tokens to every session, about $0.0049 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 2026-09-01.

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