replay-skill
Skill3 starsChanged 22 days agoMITView on GitHub
Fetch and replay one of the user's saved MosoFin skills after they name it and consent (maps to the get_my_skill MCP tool). Use when the user asks to run, replay, or re-use a saved skill or workflow by name.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- MosoFin/mosofin-mcp-pluginword for word, first seen Oct 21, 2026
Other versions1 project uses a version of this.
Word for word · 1
- MosoFin/mosofin-mcp-plugin★ 3100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository8 other files it gives its agents.
- connectionsSkill
- connectSkill
- list-skillsSkill
- list-toolsSkill
- query-workspaceSkill
- run-toolSkill
- save-skillSkill
- workspacesSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
If MosoFin tools are absent, a call returns Unknown tool, or MosoFin reports that sign-in is required: the user is not signed in to MosoFin …
- Very specific: line 33
Ask each inputs[].ask question verbatim — never silently default dates.
- Very specific: line 42
Check mock (live vs fixture) and end with a Data sources line per fetch.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Replay a saved skill
Wraps the server's get_my_skill tool (consent is server-enforced) plus
recipe execution via invoke_datasource_api_tool. Full spec:
docs/mcp-tool-spec.md §3.6.
If MosoFin tools are missing
If MosoFin tools are absent, a call returns Unknown tool, or MosoFin reports
that sign-in is required: the user is not signed in to MosoFin in this host
(this is not a company-file reconnect). Keep their request and follow
/mosofin:connect (skills/connect/SKILL.md) to get them signed in from this
conversation, then continue. Never say "refresh/reconnect". Do not invent
skill contents or figures.
Steps
- Confirm workspace via
list_workspacesif this chat has not already. - Find the skill with
get_skills; match the ask againstname/description. Present the candidate by name and wait for an explicit yes. Never auto-replay. - Only then call
get_my_skill(skill_id, confirmed="yes", workspace_id=…).confirmedmust be""or"yes"—"yes"only after the explicit chat yes. Files markedcontent_omitted: trueneed a re-call withpaths=[…]andconfirmed="yes"again. - If
references/run-recipe.jsonexists:- Ask each
inputs[].askquestion verbatim — never silently default dates. - For a
type: "data_source"input, list companies bydisplay_name(get_agent_datasources) and pass the chosendata_source_idinto every step carrying the"{data_source_id}"placeholder. A literal id in the recipe is pinned — use it as written.
- Ask each
- Execute steps in order (same
parallel_groupmay batch), substituting{workspace_id}and collected inputs, replaying data only viainvoke_datasource_api_tool— never invented numbers. - Check
mock(live vs fixture) and end with a Data sources line per fetch.
Unknown, archived, or someone else's skill_id all return the same error —
report it plainly and do not probe existence.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

