patrickmccanna.net valid
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AgentCollab
AgentCollab is a cryptographically verifiable collaboration protocol for AI agents that share a project: handoff envelopes, inventory-before-edit, conflict negotiation, specialist delegation, and a hash-manifest handshake that lets two agents prove they hold the same, unmodified rules. This domain (patrickmccanna.net) is the out-of-band trust anchor for the maintainer's signing key.
- Authority
- 46 reach 7 · trust 5 · quality 19 · freshness 15
- Tier
- listed
- llms.txt
- https://patrickmccanna.net/llms.txt
- Sections
- 2
- Links
- 7
- Size
- 2260 bytes
- Popularity rank
- #490887
- Country
- United States
- Categories
- AI and machine learning
- For agents
- Informational: content or services for people, nothing to operate
- First seen
- 2026-10-19T10:43:35.432Z
- Last checked
- 2026-10-21T04:43:02.347Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T04:42:56.161Z. Cached copy · Source on patrickmccanna.net
# AgentCollab
> AgentCollab is a cryptographically verifiable collaboration protocol for AI agents that share a project: handoff envelopes, inventory-before-edit, conflict negotiation, specialist delegation, and a hash-manifest handshake that lets two agents prove they hold the same, unmodified rules. This domain (patrickmccanna.net) is the out-of-band trust anchor for the maintainer's signing key.
Agents establish agreement by exchanging a protocol ID of the form `AgentCollab/<semver>#sha256:<16-hex-bundle-root>`, each independently computed from local files by a tool (`bin/agentcollab-id.sh`, or the Python/JS reference implementations). Verification levels: L0 (both bundles byte-identical), L1 (bundle matches its signed manifest), L2 (manifest signature verifies against the maintainer key). No mutation happens under a disputed protocol.
## Key resources
- [Repository](https://github.com/CaptainMcCrank/AgentCollab): spec, handshake tooling, schemas, conformance suite, reference implementations
- [Protocol spec](https://github.com/CaptainMcCrank/AgentCollab/blob/main/protocol/Agent_Collaboration_Protocol.md): the normative rules
- [Handshake spec](https://github.com/CaptainMcCrank/AgentCollab/blob/main/protocol/Handshake.md): manifest, bundle root, protocol ID, verification, signing
- [Tutorial](https://github.com/CaptainMcCrank/AgentCollab/blob/main/TUTORIAL.md): a complete two-agent setup in about twenty minutes
- [Trust anchor page](https://patrickmccanna.net/agentcollab): maintainer key fingerprint and verification instructions, served from a domain the repository does not control
- [Machine-readable trust store](https://patrickmccanna.net/agentcollab-allowed_signers.txt): the allowed_signers file, curl-able for `ssh-keygen -Y verify`
- [Releases](https://github.com/CaptainMcCrank/AgentCollab/releases): signed manifests attached per release
## For agents
- To verify a local copy: `./bin/agentcollab-verify.sh` in the bundle root; expect `VERIFIED [L2] AgentCollab/<ver>#sha256:<16hex>`
- To compute the protocol ID: `./bin/agentcollab-id.sh` — never recall an ID from memory; a language model cannot compute SHA-256
- The handshake proves the rules are identical and authentic; it cannot prove a model followed themRelated sites
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| Domain | Title | Category | Country | Authority | llms.txt | llms-full.txt |
|---|---|---|---|---|---|---|
| agentwebmap.com | Agent Web Map | interface AI and machine learning | FR | 60 | ✓ | ✓ |
| cloudflare.com | Cloudflare | documentation AI and machine learning Cybersecurity +1 | 85 | ✓ | ✓ | |
| adobe.com | Adobe Tools | documentation AI and machine learning Design | FR | 75 | ✓ | |
| taboola.com | Taboola.com | documentation AI and machine learning | 75 | ✓ | ✓ | |
| opera.com | The Opera browser overview | documentation Infrastructure AI and machine learning | NL | 74 | ✓ | |
| auth0.com | Auth0 | documentation AI and machine learning | 72 | ✓ | ✓ | |
| zapier.com | Zapier | documentation AI and machine learning Developer tools | 72 | ✓ | ✓ | |
| deepmind.google | Google DeepMind | documentation AI and machine learning Science and research +1 | US | 71 | ✓ | ✓ |
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