Standup Bot u 90 redaka TOML-a

Autonomni agent koji radi bez tebe, koristi samo shell + git i pamti između sesija.

standup_bot.toml

Problem

Standup je ponavljajući teret. Zaboraviš što si radio jučer. Git povijest zna, ali nemaš vremena prolaziti kroz nju svako jutro. A kad pišeš bilješke, često su općenite i slabo korisne.

Što ako agent to može napraviti umjesto tebe svaki dan u isto vrijeme, bez pitanja?

Config

Cijeli agent definiran je u standup_bot.toml - 90 redaka TOML-a. Bez Pythona. Bez JavaScripta. Bez runtime ovisnosti osim samog QueryMT-a.

Agent definition

[agent]
provider = "anthropic"
model = "claude-sonnet-4-5-20250929"
assume_mutating = false
# No mutating tools — this agent is strictly read-only
mutating_tools = []

Read-only by design

assume_mutating = false and an empty mutating_tools list means this agent can never write to disk or execute mutating commands. It reads git history and writes to its knowledge store - nothing else.

Tool selection

[agent]
tools = [
  # Git & codebase analysis (read-only)
  "read_tool", "index", "glob", "search_text", "ls", "shell",

  # Knowledge lifecycle — the magic
  "knowledge_ingest",      # Store findings
  "knowledge_query",       # Recall past standups
  "knowledge_consolidate", # Merge daily → weekly
  "knowledge_list_unconsolidated",
  "knowledge_stats",

  # Task tracking
  "create_task", "todowrite", "todoread",
]

Knowledge lifecycle tools

Three tools handle persistent memory: knowledge_ingest stores structured findings, knowledge_query retrieves them, and knowledge_consolidate merges related entries into higher-level summaries. The agent remembers across sessions automatically.

Three-layer context compaction

# Layer 1: Tool output truncation
[agent.execution.tool_output]
max_lines = 1000
max_bytes = 25600

# Layer 2: Pruning after every turn
[agent.execution.pruning]
protect_tokens = 20000

# Layer 3: AI summary on context overflow
[agent.execution.compaction]
auto = true

Git log output can be huge. These three layers keep the context window manageable: truncate tool output at 1000 lines, prune old messages while protecting recent ones, and automatically summarize the conversation when it grows too large.

Middleware: execution limits

[[middleware]]
type = "limits"
max_steps = 30    # Max tool calls per cycle
max_turns = 15    # Max conversation turns

[[middleware]]
type = "context"
warn_at_percent = 80   # Warn when 80% of context used
compact_at_percent = 90 # Auto-compact at 90%
fallback_max_tokens = 128000

Cost-bounded execution

With max_steps = 30 and max_turns = 15 each scheduled cycle has a hard ceiling on cost. The agent can't run away. Context management ensures it never hits token limits unexpectedly.

Postavljanje rasporeda

Kada pokreneš dashboard, napravi raspored iz UI-ja:

Open Session -> Schedules -> Create Schedule
Prompt: "Run a standup cycle: analyze recent git activity, ingest findings, and report."
Trigger: Interval, 86400 seconds (every 24 hours)
Max runs: 30 (one month of daily standups)
Max steps: 20

Automatic expiry

After 30 runs (one month), the schedule expires automatically. No orphaned processes. No cleanup needed.

Što se događa

Svaki dan u isto vrijeme agent autonomno pokreće ovaj ciklus:

1. Git analysis Runs git log for the last 24 hours. Reads changed files, commit messages, and diff patterns.

→

2. Pattern extraction Identifies what areas were worked on, what issues appeared, what patterns emerged.

→

3. Knowledge ingest Stores structured findings: "API layer saw heavy refactoring, 3 new endpoints added, test coverage dropped."

→

4. Standup report Generates the day's standup: what was done, what's in progress, what's blocked.

Over time, the agent builds a knowledge graph of your project's history. Weekly consolidation merges daily standups into weekly summaries. Query past standups anytime:

# Ask the agent in the dashboard:
"What were the main themes from last week's standups?"

Ključne značajke

Interval scheduling — runs on a fixed cadence, no user interaction needed
Knowledge lifecycle — ingest daily, consolidate weekly, query anytime
Autonomous execution — the bot does its job without you watching
Cost-bounded — max_steps and max_turns prevent runaway costs
Three-layer compaction — handles large git outputs gracefully
Automatic schedule expiry — no orphaned processes after the trial period

Isprobaj

# Clone and run
git clone https://github.com/querymt/querymt.git && cd querymt
cargo run --example qmtcode --features dashboard -- \
  confs/standup_bot.toml --dashboard

# In the dashboard, create a schedule:
#   Session -> Schedules -> Create Schedule
#   Prompt: "Run a standup cycle: analyze recent git activity, ingest findings, and report."
#   Trigger: Interval, 86400s (daily)
#   Max runs: 30