crewai-governance
Runtime governance middleware for CrewAI. Three features, one pip install, zero config.
What it does
| Feature | Problem it solves | How |
|---|---|---|
| Exit reports | Agents finish and their work disappears. Next run starts from scratch. | Auto-writes structured JSON after every crew run: what each agent did, what worked, token usage. |
| Overlap detection | Two crews doing the same work without knowing it. Wasted tokens, conflicting outputs. | Before kickoff, scans active crews for mandate overlap. Warns if detected. |
| Knowledge inheritance | New crew runs can't learn from past runs. Same mistakes, same dead ends. | Injects prior exit report summaries into crew context automatically. |
Install
pip install crewai-governance
Usage
from crewai import Agent, Task, Crew, Process
from crewai.project import CrewBase, before_kickoff, after_kickoff
from crewai_governance import governance_before_kickoff, governance_after_kickoff
@CrewBase
class ResearchCrew:
@before_kickoff
def before(self, inputs):
return governance_before_kickoff(
crew_name="research_crew",
mandate="research AI governance papers"
)(inputs)
@after_kickoff
def after(self, result):
return governance_after_kickoff("research_crew")(result)
# ... your agents, tasks, crew as normal
That's it. Two lines added to your existing crew class.
What happens
First run: Overlap detection finds nothing. No prior reports to inherit. Your crew runs normally. After completion, an exit report is written to .crewai-governance/exit_reports/.
Second run: Before kickoff, the middleware injects a summary of the first run's findings into the crew's context. Your agents now know what was already tried. After completion, another exit report is written.
Parallel runs: If two crews are running with overlapping mandates, overlap detection warns you before the second one starts.
Exit report structure
{
"reportId": "research_crew-1724012345678",
"crewName": "research_crew",
"completedAt": "2026-08-20T15:00:00Z",
"rawOutput": "Found 3 papers on multi-agent governance...",
"tasksOutput": [
{
"description": "Search for recent papers",
"raw": "Found papers by Smith (2026), Lee (2025)...",
"agent": "researcher"
},
{
"description": "Summarize findings",
"raw": "Key themes: coordination failures, trust...",
"agent": "writer"
}
],
"tokenUsage": {"total_tokens": 2500},
"mandateCompleted": true
}
Configuration
from crewai_governance import GovernanceConfig
config = GovernanceConfig(
storage_dir=".crewai-governance", # where data lives
max_inheritance_reports=5, # how many prior reports to inject
enable_overlap_detection=True, # turn overlap checking on/off
enable_inheritance=True, # turn inheritance on/off
)
# Pass config to hooks
governance_before_kickoff("my_crew", "my mandate", config)(inputs)
governance_after_kickoff("my_crew", config)(result)
Why this exists
Multi-agent coordination failures account for 37% of all multi-agent system failures (MAST Failure Taxonomy). The top failure modes -- infinite handoff loops, context loss, false consensus -- happen because agents have no memory of what came before and no awareness of what's running alongside them.
This package is the smallest possible intervention: give agents a record of past runs, warn when work overlaps, and let new runs learn from old ones.
License
MIT
Metadata
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