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 mattmre/EVOKORE-MCP-PUBLIC --skill improvement-cyclesgit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote 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/mattmre/evokore-mcp-public/improvement-cycles)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/improvement-cycles"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/improvement-cycles/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/mattmre/evokore-mcp-public/improvement-cycles"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/improvement-cycles.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 | $0.00014 | $0.01358 |
| Opus 5 | $0.00007 | $0.00679 |
| Sonnet 5 | $0.00003 | $0.00272 |
| Haiku 4.5 | $0.00001 | $0.00136 |
Grade A, and why
improvement-cycles 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 8d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Improvement Cycles
Structured templates for running continuous improvement cycles on AI-assisted coding sessions. Adapted from Agent33's improvement-cycle workflows.
Purpose
Improvement cycles provide a repeatable process for:
- Reviewing session metrics and outcomes
- Identifying patterns (successes and failures)
- Generating actionable improvements
- Tracking improvement adoption over time
Cycle Structure
Each improvement cycle follows four phases:
Phase 1: Metrics Collection
Automated (recommended): Use the session-retrospective-miner skill to generate a structured metrics report with no manual data gathering. The skill uses session_analyze_replay + session_work_ratio MCP tools plus direct JSONL parsing to compute all key metrics and produce actionable findings automatically:
Run session-retrospective-miner with:
time_window: "last-30-days" (or match your cycle period)
project_filter: "all" (or a specific project slug)
focus: "all"
Save output to: docs/session-logs/retro-[date].md
Then proceed to Phase 2 using the report as input.
Manual fallback (if session-retrospective-miner or its MCP tools are unavailable):
Gather quantitative data from recent sessions.
Sources:
- Session replay logs (
~/.evokore/sessions/{id}-replay.jsonl) - Evidence capture logs (
~/.evokore/sessions/{id}-evidence.jsonl) - Hook observability logs (
~/.evokore/logs/hooks.jsonl) - Git history (commits, PRs, branches)
Key Metrics:
| Metric | Source | Description |
|---|---|---|
| Tool call count | session-replay | Total tool invocations per session |
| Evidence entries | evidence-capture | Significant operations captured |
| Damage control triggers | damage-control log | Blocked or warned operations |
| Session duration | session timestamps | Time from first to last tool call |
| Files modified | git diff | Scope of changes per session |
| Test pass rate | evidence (test-result) | Ratio of passing test runs |
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.
- 8d ago First seen · 187 lines · 14 tokens per session scan A 6e7291040528
improvement-cycles is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 1,358 once invoked, about $0.0001 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 2026-09-03.
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